Neuromorphic computing is an approach to computing that is inspired by the structure and function of the human brain. A neuromorphic computer/chip is any device that uses physical artificial neurons to do computations. In recent times, the term neuromorphic has been used to describe analog, digital, mixed-mode analog/digital VLSI, and software systems that implement models of neural systems. The implementation of neuromorphic computing on the hardware level can be realized by oxide-based memristors, spintronic memories, threshold switches, transistors, among others. Training software-based neuromorphic systems of spiking neural networks can be achieved using error backpropagation, e.g., using Python based frameworks such as snnTorch, or using canonical learning rules from the biological learning literature, e.g., using BindsNet.
Carver Andress Mead is an American scientist and engineer. He currently holds the position of Gordon and Betty Moore Professor Emeritus of Engineering and Applied Science at the California Institute of Technology (Caltech), having taught there for over 40 years.
Stephen Grossberg is a cognitive scientist, theoretical and computational psychologist, neuroscientist, mathematician, biomedical engineer, and neuromorphic technologist. He is the Wang Professor of Cognitive and Neural Systems and a Professor Emeritus of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering at Boston University.
David J. Heeger is an American neuroscientist, psychologist, computer scientist, data scientist, and entrepreneur. He is a professor at New York University, Chief Scientific Officer of Statespace Labs, and Chief Scientific Officer and co-founder of Epistemic AI.
Laurent Itti is a computational neuroscientist. He received his MS in image processing from the École Nationale Supérieure des Télécommunications de Paris in 1994, and a PhD in computation and neural systems from Caltech in 2000. He is currently an associate professor of computer science, psychology, and neuroscience at the University of Southern California, where he has been since 2000.
Takeo Kanade is a Japanese computer scientist and one of the world's foremost researchers in computer vision. He is U.A. and Helen Whitaker Professor at Carnegie Mellon School of Computer Science. He has approximately 300 peer-reviewed academic publications and holds around 20 patents.
Michelle Anne Mahowald was an American computational neuroscientist in the emerging field of neuromorphic engineering. In 1996 she was inducted into the Women in Technology International Hall of Fame for her development of the Silicon Eye and other computational systems. She died by suicide at age 33.
Caltech 101 is a data set of digital images created in September 2003 and compiled by Fei-Fei Li, Marco Andreetto, Marc 'Aurelio Ranzato and Pietro Perona at the California Institute of Technology. It is intended to facilitate Computer Vision research and techniques and is most applicable to techniques involving image recognition classification and categorization. Caltech 101 contains a total of 9,146 images, split between 101 distinct object categories and a background category. Provided with the images are a set of annotations describing the outlines of each image, along with a Matlab script for viewing.
Tomaso Armando Poggio, is the Eugene McDermott professor in the Department of Brain and Cognitive Sciences, an investigator at the McGovern Institute for Brain Research, a member of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and director of both the Center for Biological and Computational Learning at MIT and the Center for Brains, Minds, and Machines, a multi-institutional collaboration headquartered at the McGovern Institute since 2013.
In image processing and computer vision, anisotropic diffusion, also called Perona–Malik diffusion, is a technique aiming at reducing image noise without removing significant parts of the image content, typically edges, lines or other details that are important for the interpretation of the image. Anisotropic diffusion resembles the process that creates a scale space, where an image generates a parameterized family of successively more and more blurred images based on a diffusion process. Each of the resulting images in this family are given as a convolution between the image and a 2D isotropic Gaussian filter, where the width of the filter increases with the parameter. This diffusion process is a linear and space-invariant transformation of the original image. Anisotropic diffusion is a generalization of this diffusion process: it produces a family of parameterized images, but each resulting image is a combination between the original image and a filter that depends on the local content of the original image. As a consequence, anisotropic diffusion is a non-linear and space-variant transformation of the original image.
Jitendra Malik is an Indian-American academic who is the Arthur J. Chick Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He is known for his research in computer vision.
Bir Bhanu is the Marlan and Rosemary Bourns Endowed University of California Presidential Chair in Engineering, the Distinguished Professor of Electrical and Computer Engineering, and Cooperative Professor of Computer Science and Engineering, Mechanical Engineering and Bioengineering, at the Marlan and Rosemary Bourns College of Engineering at the University of California, Riverside (UCR). He is the first Founding Faculty of the Marlan and Rosemary Bourns College of Engineering at UCR and served as the Founding Chair of Electrical Engineering from 1/1991 to 6/1994 and the Founding Director of the Center for Research in Intelligent Systems (CRIS) from 4/1998 to 6/2019. He has been the director of Visualization and Intelligent Systems Laboratory (VISLab) at UCR since 1991. He was the Interim Chair of the Department of Bioengineering at UCR from 7/2014 to 6/2016. Additionally, he has been the Director of the NSF Integrative Graduate Education, Research and Training (IGERT) program in Video Bioinformatics at UC Riverside. Dr. Bhanu has been the principal investigator of various programs for NSF, DARPA, NASA, AFOSR, ONR, ARO and other agencies and industries in the areas of object/target recognition, learning and vision, image/video understanding, image/video databases with applications in security, defense, intelligence, biological and medical imaging and analysis, biometrics, autonomous navigation and industrial machine vision.
Kwabena Adu Boahen is a Ghanaian-born Professor of Bioengineering and Electrical Engineering at Stanford University. He previously taught at the University of Pennsylvania.
Fei-Fei Li is a China-born American computer scientist, known for establishing ImageNet, the dataset that enabled rapid advances in computer vision in the 2010s. She is Sequoia Capital professor of computer science at Stanford University and former board director at Twitter. Li is a co-director of the Stanford Institute for Human-Centered Artificial Intelligence and a co-director of the Stanford Vision and Learning Lab. She served as the director of the Stanford Artificial Intelligence Laboratory from 2013 to 2018.
René Vidal is a Chilean electrical engineer and computer scientist who is known for his research in machine learning, computer vision, medical image computing, robotics, and control theory. He is the Herschel L. Seder Professor of the Johns Hopkins Department of Biomedical Engineering, and the founding director of the Mathematical Institute for Data Science (MINDS).
Serge Belongie is a professor of Computer Science at the University of Copenhagen, where he also serves as the head of the Danish Pioneer Centre for Artificial Intelligence. Previously, he was the Andrew H. and Ann R. Tisch Professor of Computer Science at Cornell Tech, where he also served as Associate Dean. He has also been a member of the Visiting Faculty program at Google. He is known for his contributions to the fields of computer vision and machine learning, specifically object recognition and image segmentation, with his scientific research in these areas cited over 150,000 times according to Google Scholar. Along with Jitendra Malik, Belongie proposed the concept of shape context, a widely used feature descriptor in object recognition. He has co-founded several startups in the areas of computer vision and object recognition.
Gregory D. Hager is the Mandell Bellmore Professor of Computer Science and founding director of the Johns Hopkins Malone Center for Engineering in Healthcare at Johns Hopkins University.
Pedro Felipe Felzenszwalb is a computer scientist and professor of the School of Engineering and Department of Computer Science at Brown University.
Jiebo Luo is a Chinese-American computer scientist, the Albert Arendt Hopeman Professor of Engineering and Professor of Computer Science at the University of Rochester. He is interested in artificial intelligence, data science and computer vision.
Michael J. Black is an American-born computer scientist working in Tübingen, Germany. He is a founding director at the Max Planck Institute for Intelligent Systems where he leads the Perceiving Systems Department in research focused on computer vision, machine learning, and computer graphics. He is also an Honorary Professor at the University of Tübingen.
