Learning Deep Features for Discriminative Localization Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba Computer Science and Artificial Intelligence Laboratory, MIT {bzhou,khosla,agata,oliva,torra

First Page		Document Content
Date: 2016-05-16 13:14:18 Computer vision Artificial intelligence Computational neuroscience Artificial neural networks Convolutional neural network Computational statistics Neural networks AlexNet Conference on Computer Vision and Pattern Recognition ImageNet Object detection Receptive field		Learning Deep Features for Discriminative Localization Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba Computer Science and Artificial Intelligence Laboratory, MIT {bzhou,khosla,agata,oliva,torra Add to Reading List Source URL: cnnlocalization.csail.mit.edu Download Document from Source Website File Size: 1,38 MB Share Document on Facebook

	Journal of Computational Neuroscience 18, 105–121, 2005 c 2005 Springer Science + Business Media, Inc. Manufactured in The Netherlands. A Cellular Mechanism for Graded Persistent Activity in a Model Neuron and Its Im DocID: 1vcJi - View Document
	munich Bernstein Center for Computational Neuroscience Munich DocID: 1vcv8 - View Document
	Blending computational and experimental neuroscience DocID: 1v9kZ - View Document
	Florentin Wörgötter Bernstein Center for Computational Neuroscience Göttingen Florentin Wörgötter studied biology and mathematics at the University of Düsseldorf, Germany. He received a Ph.D. degree, studying DocID: 1v914 - View Document
	Nonlinear synaptic interaction as a computational resource in the Neural Engineering Framework Andreas Stöckel, Aaron R. Voelker, Chris Eliasmith Centre for Theoretical Neuroscience, University of Waterloo {astoecke, ar DocID: 1uuia - View Document