ECE 548 - Computer Models of Cognitive Processes

Semesters Offered

TitleRubricSectionCRNTypeHoursTimesDaysLocationInstructor
Models of Cognitive ProcessesCS548R64710LEC1400 - 1515 T R  1131 Siebel Center for Comp Sci Wai-Tat Fu
Models of Cognitive ProcessesECE548R64711LEC1400 - 1515 T R  1131 Siebel Center for Comp Sci Wai-Tat Fu

Official Description

Course Information: Same as CS 548. See CS 548.

Subject Area

Biomedical Imaging, Bioengineering, and Acoustics

Course Director

Computer Science

Description

Formal models and concepts in vision and language; detailed analysis of computer vision, language, and learning problems; relevant psychological results and linguistic systems; and survey of the state of the art in artificial intelligence.

Notes

Same as CS 548.

Topics

  • Relevant psychological results in vision: the frog's eye; the cat's visual system; human visual phenomena; neural net models and neurophysiological results
  • Computer vision systems: adaptive systems; perceptrons; heuristic systems (Guzman, Chang, Agin, Binford); structured systems (Huffman, Clowes, Waltz); model-driven systems (Shirai, Tennenbaum)
  • Representation of visual information: pattern recognition and templates; polyhedra, line drawings, structural descriptions; natural objects and scenes with motion
  • Frame-systems: Is vision symbolic? The importance of context; cultural factors in perception, relationships between perception and language; reasoning
  • Linguistics: historical perspective and problems of human and machine translation; transformational grammars and syntax; augmented transition networks; systemic grammars, case grammars, and semantics
  • Computer language systems: analysis of programs by Weizenbaum, Bobrow, Quillian, Simmons, Woods, Schank, Winograd, Martin, Rumelhart and Norman
  • Current problems and research: learning and program meta-description (Piaget-Sussman); the natue of intelligence; language of chimpanzees; belief systems and abiguity (Charniak, McCarthy, Colgy)

Detailed Description and Outline

Topics:

  • Relevant psychological results in vision: the frog's eye; the cat's visual system; human visual phenomena; neural net models and neurophysiological results
  • Computer vision systems: adaptive systems; perceptrons; heuristic systems (Guzman, Chang, Agin, Binford); structured systems (Huffman, Clowes, Waltz); model-driven systems (Shirai, Tennenbaum)
  • Representation of visual information: pattern recognition and templates; polyhedra, line drawings, structural descriptions; natural objects and scenes with motion
  • Frame-systems: Is vision symbolic? The importance of context; cultural factors in perception, relationships between perception and language; reasoning
  • Linguistics: historical perspective and problems of human and machine translation; transformational grammars and syntax; augmented transition networks; systemic grammars, case grammars, and semantics
  • Computer language systems: analysis of programs by Weizenbaum, Bobrow, Quillian, Simmons, Woods, Schank, Winograd, Martin, Rumelhart and Norman
  • Current problems and research: learning and program meta-description (Piaget-Sussman); the natue of intelligence; language of chimpanzees; belief systems and abiguity (Charniak, McCarthy, Colgy)

Same as CS 548.

Texts

Jude Shavlik and Thomas Dietterich, Readings in Machine Learning, Morgan Kaufman.

Last updated

2/13/2013