際際滷shows by User: devashishsarkar / http://www.slideshare.net/images/logo.gif 際際滷shows by User: devashishsarkar / Wed, 04 Nov 2015 22:49:55 GMT 際際滷Share feed for 際際滷shows by User: devashishsarkar Md Mushfiqul Alam: Biological, NeuralNet Approaches to Recognition, Gain Control /slideshow/md-mushfiqul-alam-biological-neuralnet-approaches-to-recognition-gain-control/54755576 mushfiq-biologicalneuralnetapproachestorecognitiongaincontrol-151104224955-lva1-app6891
Mushfiq recently finished his PhD in Electrical and Computer Engineering from Oklahoma State University. In this video, he presents: (1) A database (the largest of its kind) created by a well-controlled psychophysical study using natural scenes, (2) How the most advanced biologically plausible model of V1 and a trained convolutional-neural-network fails to capture the recognition factors, and (3) How a computational approach can be adopted to integrate the recognition into the V1 responses. He also discusses and shows how such a model can be integrated to have a better video compression algorithm.]]>
Mushfiq recently finished his PhD in Electrical and Computer Engineering from Oklahoma State University. In this video, he presents: (1) A database (the largest of its kind) created by a well-controlled psychophysical study using natural scenes, (2) How the most advanced biologically plausible model of V1 and a trained convolutional-neural-network fails to capture the recognition factors, and (3) How a computational approach can be adopted to integrate the recognition into the V1 responses. He also discusses and shows how such a model can be integrated to have a better video compression algorithm.]]> Wed, 04 Nov 2015 22:49:55 GMT /slideshow/md-mushfiqul-alam-biological-neuralnet-approaches-to-recognition-gain-control/54755576 devashishsarkar@slideshare.net(devashishsarkar) Md Mushfiqul Alam: Biological, NeuralNet Approaches to Recognition, Gain Control devashishsarkar Mushfiq recently finished his PhD in Electrical and Computer Engineering from Oklahoma State University. In this video, he presents: (1) A database (the largest of its kind) created by a well-controlled psychophysical study using natural scenes, (2) How the most advanced biologically plausible model of V1 and a trained convolutional-neural-network fails to capture the recognition factors, and (3) How a computational approach can be adopted to integrate the recognition into the V1 responses. He also discusses and shows how such a model can be integrated to have a better video compression algorithm. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mushfiq-biologicalneuralnetapproachestorecognitiongaincontrol-151104224955-lva1-app6891-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Mushfiq recently finished his PhD in Electrical and Computer Engineering from Oklahoma State University. In this video, he presents: (1) A database (the largest of its kind) created by a well-controlled psychophysical study using natural scenes, (2) How the most advanced biologically plausible model of V1 and a trained convolutional-neural-network fails to capture the recognition factors, and (3) How a computational approach can be adopted to integrate the recognition into the V1 responses. He also discusses and shows how such a model can be integrated to have a better video compression algorithm.
Md Mushfiqul Alam: Biological, NeuralNet Approaches to Recognition, Gain Control from devashishsarkar
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