In many recent object recognition systems feature extraction stages are generally composed of a filter bank a non linear transformation and some sort of feature pooling layer. What is the best multi stage architecture for object recognition.
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An Overview Of Object Detection One Stage Methods
In many recent object recognition systems feature extraction stages are generally composed of a filter bank a non linear transformation and some sort of feature pooling layer.
What is the best multi stage architecture for object recognition. At articlejarrett2009whatit titlewhat is the best multi stage architecture for object recognition authorkevin jarrett and koray kavukcuoglu and marcaurelio ranzato and yann lecun journal2009 ieee 12th international conference on computer vision year2009 pages2146 2153. What is the best multi stage architecture for object recognition. Request pdf on researchgate what is the best multi stage architecture for object recognition.
Kevin jarrett koray kavukcuoglu marcaurelio ranzato and yann lecun the courant institute of mathematical sciences new york university 715 broadway new york ny 10003 usa koray at csnyuedu abstract in many recent object recognition systems feature ex. Following the psd method 8 9 5 we use an encoder to approximate the optimal sparse code z. What is the best multi stage architecture for object recognition.
Is there any advantage to using an architecture with two stages of feature extraction rather than one. We show that using non linearities that include rectification and local contrast normalization is the single most important ingredient for good accuracy on object recognition benchmarks. In particular we show how we can use this trainable module as a component in a larger globally trained system with a exible multi stage architecture.
Kevin jarrett koray kavukcuoglu marcaurelio ranzato and yann lecun the courant institute of mathematical sciences new york university 715 broadway new york ny 10003 usa koray at csnyuedu abstract in many recent object recognition systems feature ex. Most systems use only one stage of feature extraction in which the filters are hard wired or two stages where the filters in one or both stages are learned in supervised or unsupervised mode. In many recent object recognition systems feature extraction stages are generally composed of a filter bank a non linear transformation and some sort of feature pooling layer.
Most systems use only one stage of feature extraction in which the filters are hard wired. In many recent object recognition systems feature extraction stages are generally composed of a. What is the best multi stage architecture for object recognition.
What is the best multi stage architecture for object recognition. What is the best multi stage architecture for object recognition kevin jarrett koray kavukcuoglu marc aurelio ranzato and yann lecun presented by lingbo li. To extend the use of discriminative dictionaries to a larger class of recognition sys tems.
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