Verified email at cs.stanford.edu - Homepage. Li Fei-Fei. Fei-Fei Li . Machine Learning for Healthcare (MLHC) 2018, Stanford, CA, August 17-18, 2018 L. Fei-Fei, R. Fergus and P. Perona. Her career at Stanford started in 2009 as an assistant professor, until she became a full professor of Computer Science by 2017. Hello! Dr. Li’s main research areas are in machine learning, deep learning, computer vision, and cognitive and computational neuroscience. We are interested in both inferring the semantics of the world and extracting 3D structure. Why does natural scene recognition require little attention? Cited by. arXiv:1412.2306 (cs) [Submitted on 7 Dec 2014 , last revised 14 Apr 2015 (this version, v2)] Title: Deep Visual-Semantic Alignments for Generating Image Descriptions. Fei-Fei Li’s current research interests include cognitively inspired AI, machine learning, deep learning, computer vision and AI+healthcare especially ambient intelligent systems for healthcare delivery. The difficulty is that computers see only digital image representations. During her last visit to Beijing, the professor of Stanford University drew much attention from both academy and industry here; NSR took the opportunity to interview Professor Li. 5) L. Fei-Fei, R. Fergus and P. Perona. Fei-Fei Li Professor, Computer Science Dept, Stanford; Co-Director, Stanford Human-Centered AI Institute Stanford, California 316 connections Year; Imagenet: A large-scale hierarchical image database. Fei-Fei Li, associate professor of computer science. Computer Vision 2 Part 17 –CNNs for Video Analysis Recap: RNNs for Text Generation •RNN for text generation Slide credit: Andrej Karpathy, Fei-Fei Li Image source: Andrej Karpathy Word embedding (300D vector for each word) Hidden layer (e.g., 500D vectors) 10,001D class scores (Softmax over 10k words and a special token) After finishing her studies, Fei-Fei Li was an assistant professor in the Electrical & Computer Engineering department at University of Illinois and also in the Computer Science department at Princeton University. “If we want machines to think, we need to teach them to see.” -Fei Fei Li, Director of Stanford AI Lab and Stanford Vision Lab. Download PDF Abstract: Visual relationships capture a wide variety of interactions between pairs of objects in images (e.g. Diverted from artificial intelligence, research in the field of CV began around the 1960s. Zelun Luo*, Jun-Ting Hsieh*, Niranjan Balachandar, Serena Yeung, Guido Pusiol, Jay Luxenberg, Grace Li, Li-Jia Li, N. Lance Downing, Arnold Milstein, Li Fei-Fei. Proc. These two databases – one of objects and the other of scenes – served as training material. Artificial Intelligence Machine Learning Computer Vision Neuroscience. Computer vision researchers at Princeton focus on developing artificially intelligent systems that are able to reason about the visual world. arXiv:1608.00187 (cs) [Submitted on 31 Jul 2016] Title: Visual Relationship Detection with Language Priors. Multi-view Object Categorization and Pose Estimation Studies in Computational Intelligence- Computer Vision Savarese, S., Fei-Fei, L. 2010: 1; What, Where and Who? Journal of Vision, in press. Humans can understand the semantic meaning of an image, but machines rarely do. • When we “see” something, what does it involve? Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Origins of computer vision: an MIT undergraduate summer project . Departments of Computer Science, Stanford, CA, Daniel L. K. Yamins. Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Sounds logical and obvious, right? Dr. Fei-Fei Li’s main research areas are in machine learning, deep learning, computer vision and cognitive and computational neuroscience. In the past she has also worked on cognitive and computational neuroscience. We are tackling fundamental open problems in computer vision research and are intrigued by visual functionalities that give rise to semantically meaningful interpretations of the visual world. Authors: Cewu Lu, Ranjay Krishna, Michael Bernstein, Li Fei-Fei. Sort. Computer Vision and Image Understanding. Fei-Fei Li (simplified Chinese: 李飞飞; traditional Chinese: 李飛飛; born 1976) is a Chinese-born American computer scientist, non-profit executive, and writer.She is the Sequoia Capital Professor of Computer Science at Stanford University. free access. The Stanford Vision and Learning Lab (SVL) at Stanford is directed by Professors Fei-Fei Li, Juan Carlos Niebles, Silvio Savarese and Jiajun Wu. Measuring the cost of deploying top-down visual attention. A Bayesian approach to unsupervised One-Shot learning of Object categories. 加到我收藏. Professor of Computer Science, Stanford University. Departments of Psychology, Stanford, CA and Departments of Computer Science, Stanford, CA and Wu Tsai Neurosciences Institute, Stanford, CA December 2018 NIPS'18: Proceedings of the 32nd International Conference on Neural Information Processing Systems. Fei-Fei Li & Justin Johnson & SerenaYeung Lecture 11-Vector: 4096 Fully-Connected: 4096 to 1000 May 10, 2017 So far: Image Classification Slide by: Justin Johnson. Then Fei-Fei Li arrived at Stanford. CVPR, Workshop on Generative-Model Based Vision. She has published nearly 200 scientific articles in top-tier journals and conferences, including Nature, PNAS, Journal of Neuroscience, CVPR, ICCV, NIPS, ECCV, ICRA, IROS, RSS, IJCV, IEEE-PAMI, New England Journal of Medicine, etc. Li Fei-Fei. Articles Cited by Co-authors. I’m very excited that you are here! An unprecedented thought leader in AI through her revolutionary computer vision research, Fei-Fei has had transformational industry impact democratizing AI, pioneering future technological innovations, and advocating diversity in STEM and AI internationally. Authors: Andrej Karpathy, Li Fei-Fei. L. G. Roberts, Machine Perception of Three Dimensional Solids, Ph.D. thesis, MIT Department of … 4) D. Walther, L. Fei-Fei, and C. Koch. 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