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Harvard Neuro 130/230: Visual recognition (Fall 2021)

Neuro 130 Visual Recognition
Harvard Neuro 130/230: Visual Recognition

Link to class web site

Visual recognition is essential for most everyday tasks including navigation, reading and socialization. Visual pattern recognition is also important for many engineering applications such as automatic analysis of clinical images, face recognition by computers, security tasks and automatic navigation. In spite of the enormous increase in computational power over the last decade, humans still outperform the most sophisticated engineering algorithms in visual recognition tasks. In this course, we will examine how circuits of neurons in visual cortex represent and transform visual information. The course will cover the following topics: functional architecture of visual cortex, lesion studies, physiological experiments in humans and animals, visual consciousness, computational models of visual object recognition, computer vision algorithms.

The class will follow this textbook:

Kreiman G (to appear, 2021). Biological and Computer Vision. Cambridge University Press.

Kreiman Biological and Computer Vision
Biological and Computer Vision. Cambridge University Press 2021
Categories
Kreiman Lab News

Kreiman lab introduction for incoming graduate students

September 2020

Categories
Kreiman Lab News

Neuro 130/230: Visual object recognition (Fall 2019)

Fall 2019. Neuro 130/230. Visual object recognition: Computational and biophysical mechanisms

Visual recognition is essential for most everyday tasks including navigation, reading and socialization. Visual pattern recognition is also important for many engineering applications such as automatic analysis of clinical images, face recognition by computers, security tasks and automatic navigation. In spite of the enormous increase in computational power over the last decade, humans still outperform the most sophisticated engineering algorithms in visual recognition tasks. In this course, we will examine how circuits of neurons in visual cortex represent and transform visual information. The course will cover the following topics: functional architecture of visual cortex, lesion studies, physiological experiments in humans and animals, visual consciousness, computational models of visual object recognition, computer vision algorithms.

Textbook for the class:

Kreiman Biological and Computer Vision
Biological and Computer Vision. Cambridge University Press 2021