Imagine a world where machines can see and understand the world the way humans do. Rapid progress in artificial intelligence has led to smartphones that recognize faces, cars that detect pedestrians, and algorithms that suggest diagnoses from clinical images, among many other applications. The success of computer vision is founded on a deep understanding of the neural circuits in the brain responsible for visual processing. This book introduces the neuroscientific study of neuronal computations in visual cortex alongside of the psychological understanding of visual cognition and the burgeoning field of biologically-inspired artificial intelligence. Topics include the neurophysiological investigation of visual cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among others. It is an ideal resource for students and researchers looking to build bridges across different approaches to studying and developing visual systems.
Congratulations to Mengmi Zhang in her successful defense of her Ph.D. thesis!
Mengmi Zhang. Computational Models of Bottom-up and Top-down Attention. National University of Singapore (2019).
See also Zhang’s recent publications:
Gupta SK, Zhang M, Wu CC, Wolfe JM, Kreiman G (2021). Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases. NeurIPS arXiv 2106.02953 PDF
Zhang M, Tseng C, Kreiman G. (2020) Putting visual object recognition in context. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit (CVPR) 12982-12991 PDF
Zhang M, Kreiman G (2021). Beauty is in the eye of the machine. Nature Human Behavior 5:1-2 PDF
Bomatter P, Zhang M, Karev D, Madan S, Tseng C, Kreiman G (2021). When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes. International Conference on Computer Vision (ICCV) arXiv 2104.02215 PDF
Zhang M, Feng J, Ma KT, Lim JH, Zhao Q, Kreiman G. (2018) Finding any Waldo: zero-shot invariant and efficient visual search. Nature Communications, 9:3730. PDF
Lecture given by Prof. Gabriel Kreiman at Harvard Neuro 140 (Biological and Artificial Intelligence)