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6.801 Machine Vision (MIT) 6.801 Machine Vision (MIT)

Description

Machine Vision provides an intensive introduction to the process of generating a symbolic description of an environment from an image. Lectures describe the physics of image formation, motion vision, and recovering shapes from shading. Binary image processing and filtering are presented as preprocessing steps. Further topics include photogrammetry, object representation alignment, analog VLSI and computational vision. Applications to robotics and intelligent machine interaction are discussed. Machine Vision provides an intensive introduction to the process of generating a symbolic description of an environment from an image. Lectures describe the physics of image formation, motion vision, and recovering shapes from shading. Binary image processing and filtering are presented as preprocessing steps. Further topics include photogrammetry, object representation alignment, analog VLSI and computational vision. Applications to robotics and intelligent machine interaction are discussed.

Subjects

machine vision | machine vision | image formation physics | image formation physics | image analysis | image analysis | binary image processing | binary image processing | image filtering | image filtering | recovering | recovering | shape | shape | lightness | lightness | orientation | orientation | motion | motion | photometric stereo | photometric stereo | extended Gaussian | extended Gaussian | environment interaction | environment interaction | motion vision | motion vision | shape from shading | shape from shading | photogrammetry | photogrammetry | stereo | stereo | object representation alignment | object representation alignment | analog VLSI | analog VLSI | computational vision | computational vision | robot vision | robot vision

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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HST.583 Functional Magnetic Resonance Imaging: Data Acquisition and Analysis (MIT) HST.583 Functional Magnetic Resonance Imaging: Data Acquisition and Analysis (MIT)

Description

This team-taught multidisciplinary course provides information relevant to the conduct and interpretation of human brain mapping studies. It begins with in-depth coverage of the physics of image formation, mechanisms of image contrast, and the physiological basis for image signals. Parenchymal and cerebrovascular neuroanatomy and application of sophisticated structural analysis algorithms for segmentation and registration of functional data are discussed. Additional topics include: fMRI experimental design including block design, event related and exploratory data analysis methods, and building and applying statistical models for fMRI data; and human subject issues including informed consent, institutional review board requirements and safety in the high field environment. Additional Facul This team-taught multidisciplinary course provides information relevant to the conduct and interpretation of human brain mapping studies. It begins with in-depth coverage of the physics of image formation, mechanisms of image contrast, and the physiological basis for image signals. Parenchymal and cerebrovascular neuroanatomy and application of sophisticated structural analysis algorithms for segmentation and registration of functional data are discussed. Additional topics include: fMRI experimental design including block design, event related and exploratory data analysis methods, and building and applying statistical models for fMRI data; and human subject issues including informed consent, institutional review board requirements and safety in the high field environment. Additional Facul

Subjects

medical imaging | medical imaging | medical lab | medical lab | medical technology | medical technology | magnetic resonance imaging | magnetic resonance imaging | MRI | MRI | fMRI | fMRI | signal processing | signal processing | human brain mapping | human brain mapping | function | function | image formation physics | image formation physics | metabolism | metabolism | psychology | psychology | physiology | physiology | image signals | image signals | image processing | image processing | parenchymal | parenchymal | cerebrovascular neuroanatomy | cerebrovascular neuroanatomy | neurology | neurology | functional data analysis | functional data analysis | experimental design | experimental design | statistical models | statistical models | human subjects | human subjects | informed consent | informed consent | institutional review board requirements | institutional review board requirements | safety | safety | medical | medical | brain scan | brain scan | brain imaging | brain imaging | DTI | DTI | vision | vision

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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6.881 Representation and Modeling for Image Analysis (MIT) 6.881 Representation and Modeling for Image Analysis (MIT)

Description

Most algorithms in computer vision and image analysis can be understood in terms of two important components: a representation and a modeling/estimation algorithm. The representation defines what information is important about the objects and is used to describe them. The modeling techniques extract the information from images to instantiate the representation for the particular objects present in the scene. In this seminar, we will discuss popular representations (such as contours, level sets, deformation fields) and useful methods that allow us to extract and manipulate image information, including manifold fitting, markov random fields, expectation maximization, clustering and others. For each concept -- a new representation or an estimation algorithm -- a lecture on the mathematical f Most algorithms in computer vision and image analysis can be understood in terms of two important components: a representation and a modeling/estimation algorithm. The representation defines what information is important about the objects and is used to describe them. The modeling techniques extract the information from images to instantiate the representation for the particular objects present in the scene. In this seminar, we will discuss popular representations (such as contours, level sets, deformation fields) and useful methods that allow us to extract and manipulate image information, including manifold fitting, markov random fields, expectation maximization, clustering and others. For each concept -- a new representation or an estimation algorithm -- a lecture on the mathematical f

Subjects

computer vision | computer vision | image analysis | image analysis | representation algorithm | representation algorithm | modeling | modeling | estimation algorithm | estimation algorithm | information | information | objects | objects | modeling techniques | modeling techniques | images | images | representations | representations | contours | contours | level sets | level sets | deformation fields | deformation fields | image information | image information | manifold fitting | manifold fitting | markov random fields | markov random fields | expectation maximization | expectation maximization | clustering | clustering | mathematical foundations | mathematical foundations | medical and biological imaging | medical and biological imaging

License

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MAS.963 Special Topics: Computational Camera and Photography (MIT) MAS.963 Special Topics: Computational Camera and Photography (MIT)

Description

A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. In this course we will study this emerging multi-disciplinary field at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded — beyond those present in traditional photographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. In this course we will study this emerging multi-disciplinary field at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded — beyond those present in traditional photographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information

Subjects

signal processing; applied optics; Computer graphics; computer vision; online photo; digital photography; digital imaging; visual art image processing | signal processing; applied optics; Computer graphics; computer vision; online photo; digital photography; digital imaging; visual art image processing | image sensor | image sensor | image reconstruction | image reconstruction | medical imaging | medical imaging | mblog | mblog | biomimetics | biomimetics | lens | lens | spectrum | spectrum | multi-spectral | multi-spectral | 3D imaging | 3D imaging | thermal imaging | thermal imaging | high-speed imaging | high-speed imaging | polarization | polarization

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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HST.583 Functional Magnetic Resonance Imaging: Data Acquisition and Analysis (MIT) HST.583 Functional Magnetic Resonance Imaging: Data Acquisition and Analysis (MIT)

Description

This team taught, multidisciplinary course covers the fundamentals of magnetic resonance imaging relevant to the conduct and interpretation of human brain mapping studies. The challenges inherent in advancing our knowledge about brain function using fMRI are presented first to put the work in context. The course then provides in depth coverage of the physics of image formation, mechanisms of image contrast, and the physiological basis for image signals. Parenchymal and cerebrovascular neuroanatomy and application of sophisticated structural analysis algorithms for segmentation and registration of functional data are discussed. Additional topics include fMRI experimental design including block design, event related and exploratory data analysis methods, building and applying statistical mod This team taught, multidisciplinary course covers the fundamentals of magnetic resonance imaging relevant to the conduct and interpretation of human brain mapping studies. The challenges inherent in advancing our knowledge about brain function using fMRI are presented first to put the work in context. The course then provides in depth coverage of the physics of image formation, mechanisms of image contrast, and the physiological basis for image signals. Parenchymal and cerebrovascular neuroanatomy and application of sophisticated structural analysis algorithms for segmentation and registration of functional data are discussed. Additional topics include fMRI experimental design including block design, event related and exploratory data analysis methods, building and applying statistical mod

Subjects

medical lab | medical lab | medical technology | medical technology | magnetic resonance imaging | magnetic resonance imaging | fMRI | fMRI | signal processing | signal processing | human brain mapping | human brain mapping | function | function | image formation physics | image formation physics | metabolism | metabolism | psychology | psychology | image signals | image signals | parenchymal | parenchymal | cerebrovascular neuroanatomy | cerebrovascular neuroanatomy | functional data analysis | functional data analysis | experimental design | experimental design | statistical models | statistical models | human subjects | human subjects | informed consent | informed consent | institutional review board requirements | institutional review board requirements | safety | safety | medical | medical | brain scan | brain scan

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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6.801 Machine Vision (MIT)

Description

Machine Vision provides an intensive introduction to the process of generating a symbolic description of an environment from an image. Lectures describe the physics of image formation, motion vision, and recovering shapes from shading. Binary image processing and filtering are presented as preprocessing steps. Further topics include photogrammetry, object representation alignment, analog VLSI and computational vision. Applications to robotics and intelligent machine interaction are discussed.

Subjects

machine vision | image formation physics | image analysis | binary image processing | image filtering | recovering | shape | lightness | orientation | motion | photometric stereo | extended Gaussian | environment interaction | motion vision | shape from shading | photogrammetry | stereo | object representation alignment | analog VLSI | computational vision | robot vision

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.801 Machine Vision (MIT)

Description

Machine Vision provides an intensive introduction to the process of generating a symbolic description of an environment from an image. Lectures describe the physics of image formation, motion vision, and recovering shapes from shading. Binary image processing and filtering are presented as preprocessing steps. Further topics include photogrammetry, object representation alignment, analog VLSI and computational vision. Applications to robotics and intelligent machine interaction are discussed.

Subjects

machine vision | image formation physics | image analysis | binary image processing | image filtering | recovering | shape | lightness | orientation | motion | photometric stereo | extended Gaussian | environment interaction | motion vision | shape from shading | photogrammetry | stereo | object representation alignment | analog VLSI | computational vision | robot vision

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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18.304 Undergraduate Seminar in Discrete Mathematics (MIT) 18.304 Undergraduate Seminar in Discrete Mathematics (MIT)

Description

This course is a student-presented seminar in combinatorics, graph theory, and discrete mathematics in general. Instruction and practice in written and oral communication is emphasized, with participants reading and presenting papers from recent mathematics literature and writing a final paper in a related topic. This course is a student-presented seminar in combinatorics, graph theory, and discrete mathematics in general. Instruction and practice in written and oral communication is emphasized, with participants reading and presenting papers from recent mathematics literature and writing a final paper in a related topic.

Subjects

discrete math; discrete mathematics; discrete; math; mathematics; seminar; presentations; student presentations; oral; communication; stable marriage; dych; emergency; response vehicles; ambulance; game theory; congruences; color theorem; four color; cake cutting; algorithm; RSA; encryption; numberical integration; sorting; post correspondence problem; PCP; ramsey; van der waals; fibonacci; recursion; domino; tiling; towers; hanoi; pigeonhole; principle; matrix; hamming; code; hat game; juggling; zero-knowledge; proof; repeated games; lewis carroll; determinants; infinitude of primes; bridges; konigsberg; koenigsberg; time series analysis; GARCH; rational; recurrence; relations; digital; image; compression; quantum computing | discrete math; discrete mathematics; discrete; math; mathematics; seminar; presentations; student presentations; oral; communication; stable marriage; dych; emergency; response vehicles; ambulance; game theory; congruences; color theorem; four color; cake cutting; algorithm; RSA; encryption; numberical integration; sorting; post correspondence problem; PCP; ramsey; van der waals; fibonacci; recursion; domino; tiling; towers; hanoi; pigeonhole; principle; matrix; hamming; code; hat game; juggling; zero-knowledge; proof; repeated games; lewis carroll; determinants; infinitude of primes; bridges; konigsberg; koenigsberg; time series analysis; GARCH; rational; recurrence; relations; digital; image; compression; quantum computing | discrete math | discrete math | discrete mathematics | discrete mathematics | discrete | discrete | math | math | mathematics | mathematics | seminar | seminar | presentations | presentations | student presentations | student presentations | oral | oral | communication | communication | stable marriage | stable marriage | dych | dych | emergency | emergency | response vehicles | response vehicles | ambulance | ambulance | game theory | game theory | congruences | congruences | color theorem | color theorem | four color | four color | cake cutting | cake cutting | algorithm | algorithm | RSA | RSA | encryption | encryption | numberical integration | numberical integration | sorting | sorting | post correspondence problem | post correspondence problem | PCP | PCP | ramsey | ramsey | van der waals | van der waals | fibonacci | fibonacci | recursion | recursion | domino | domino | tiling | tiling | towers | towers | hanoi | hanoi | pigeonhole | pigeonhole | principle | principle | matrix | matrix | hamming | hamming | code | code | hat game | hat game | juggling | juggling | zero-knowledge | zero-knowledge | proof | proof | repeated games | repeated games | lewis carroll | lewis carroll | determinants | determinants | infinitude of primes | infinitude of primes | bridges | bridges | konigsberg | konigsberg | koenigsberg | koenigsberg | time series analysis | time series analysis | GARCH | GARCH | rational | rational | recurrence | recurrence | relations | relations | digital | digital | image | image | compression | compression | quantum computing | quantum computing

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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01_00093464 Convair 880 165-62 Cathay Pacific in flight 13Mar62 01_00093464 Convair 880 165-62 Cathay Pacific in flight 13Mar62

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | donated | donated | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093599 Convair 990 678-61 NASA 1961 01_00093599 Convair 990 678-61 NASA 1961

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | airliner | airliner | donated | donated | permanently | permanently | stored | stored | a | a | convair990 | convair990 | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093578 Convair 990 070-62 American AL Royal Coachman LAX 15Jan62 01_00093578 Convair 990 070-62 American AL Royal Coachman LAX 15Jan62

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | americanairlines | americanairlines | information | information | dynamics | dynamics | aa | aa | donated | donated | convair | convair | permanently | permanently | stored | stored | astrojet | astrojet | a | a | convair990 | convair990 | cv990 | cv990 | sdasm | sdasm | filerepository | filerepository | convaircv990 | convaircv990 | n5605 | n5605 | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093571 Convair 990 025-62 Swissair in flight 8Jan62 01_00093571 Convair 990 025-62 Swissair in flight 8Jan62

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | airliner | airliner | donated | donated | swissair | swissair | permanently | permanently | stored | stored | a | a | convair990 | convair990 | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093570 Convair 990 025-62 Swissair in flight 8Jan62 01_00093570 Convair 990 025-62 Swissair in flight 8Jan62

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | airliner | airliner | donated | donated | permanently | permanently | stored | stored | a | a | convair990 | convair990 | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093567 Convair 990 025-62 Swissair in flight 8Jan62 01_00093567 Convair 990 025-62 Swissair in flight 8Jan62

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | donated | donated | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093544 Convair 880 1056-61 JAL 4Aug61 01_00093544 Convair 880 1056-61 JAL 4Aug61

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from | from | japan | japan | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | jet | jet | diego | diego | can | can | images | images | be | be | passenger | passenger | these | these | airlines | airlines | information | information | dynamics | dynamics | donated | donated | convair | convair | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | ja8021 | ja8021 | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093534 Convair 880 950-61 Swissair 8Aug61 01_00093534 Convair 880 950-61 Swissair 8Aug61

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | donated | donated | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093527 Convair 880-42 interior photos 01_00093527 Convair 880-42 interior photos

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | donated | donated | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093526 Convair 880-42 interior photos 01_00093526 Convair 880-42 interior photos

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | donated | donated | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093499 Convair 880-17 Delta AL 01_00093499 Convair 880-17 Delta AL

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | donated | donated | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093468 Convair 880 168-62 Cathay Pacific in flight 13Mar62 01_00093468 Convair 880 168-62 Cathay Pacific in flight 13Mar62

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | donated | donated | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093467 Convair 880 168-62 Cathay Pacific in flight 13Mar62 01_00093467 Convair 880 168-62 Cathay Pacific in flight 13Mar62

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | donated | donated | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093469Convair 880 168-62 Cathay Pacific in flight 13Mar62 01_00093469Convair 880 168-62 Cathay Pacific in flight 13Mar62

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | donated | donated | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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01_00093465 Convair 880 166-62 Cathay Pacific in flight 13Mar62 01_00093465 Convair 880 166-62 Cathay Pacific in flight 13Mar62

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from | from | museum | museum | digital | digital | that | that | with | with | image | image | please | please | space | space | air | air | tag | tag | diego | diego | can | can | images | images | be | be | these | these | information | information | dynamics | dynamics | donated | donated | permanently | permanently | stored | stored | a | a | sdasm | sdasm | filerepository | filerepository | relnofollowsan | relnofollowsan | convairgeneral | convairgeneral

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9.913 Pattern Recognition for Machine Vision (MIT) 9.913 Pattern Recognition for Machine Vision (MIT)

Description

The applications of pattern recognition techniques to problems of machine vision is the main focus for this course. Topics covered include, an overview of problems of machine vision and pattern classification, image formation and processing, feature extraction from images, biological object recognition, bayesian decision theory, and clustering. The applications of pattern recognition techniques to problems of machine vision is the main focus for this course. Topics covered include, an overview of problems of machine vision and pattern classification, image formation and processing, feature extraction from images, biological object recognition, bayesian decision theory, and clustering.

Subjects

comonent analysis | comonent analysis | PCA | PCA | ICA | ICA | fourier analysis | fourier analysis | vision | vision | machine vision | machine vision | pattern matching | pattern matching | pattern analysis | pattern analysis | pattern recognition | pattern recognition | scene analysis | scene analysis | tracking | tracking | feature extraction | feature extraction | color | color | color space | color space | clustering | clustering | bayesian decisions | bayesian decisions | gesture recognition | gesture recognition | action recognition | action recognition | image processing | image processing | image formation | image formation | density estimation | density estimation | classification | classification | morphable models | morphable models | component analysis | component analysis

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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How digital camera images are formed

Description

This resource is a learning object designed for Level 3 students of General art and design. It illustrates the key concepts surrounding the formation of digital images. It explains what digital images are and the fundamental elements that they consist of. It shows how colour depth, resolution and format all affect the image and allows the user to change attributes and view results. It also covers the concepts of image size in relation to resolution and the effects of image manipulation. The learning objects may be used as part of a group classroom activity, or as part of the individual study programme of the learner. The content of the objects has been designed to apply equally to the English (Level 3) and Scottish (Highers) General art and design curricula.

Subjects

art and design | digital images | image resolution | colour depth | image manipulation | image format | bitmap | vectors | Arts and Crafts | Creative Arts and Design | Design and delivery of programmes | Learning | UK EL03 = SCQF 3 | Level 3 | Entry level 2 | NICAT Entry | Access 3 | Foundation SG | UK EL04 = SCQF 4 | Foundational Level | NICAT 1 | CQFW 1 | Foundation | GCSE D-G | NVQ 1 | Intermediate 1 | | UK EL05 = SCQF 5 | Intermediate level | Intermediate | NICAT 2 | CQFW 2 | Intermediate | GSCE A-C | NVQ 2 | | design | W000

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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