Transcription of Spatial Pyramid Pooling in Deep Convolutional Networks for ...
{{id}} {{{paragraph}}}
Example: barber
Spatial Pyramid Pooling in Deep Convolutional Networks for ...
1 Spatial Pyramid Pooling in Deep ConvolutionalNetworks for visual RecognitionKaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian SunAbstract Existing deep Convolutional neural Networks (CNNs) require a fixed-size ( , 224 224) input image. This require-ment is artificial and may reduce the recognition accuracy for the images or sub-images of an arbitrary size/scale. In thiswork, we equip the Networks with another Pooling strategy, Spatial Pyramid Pooling , to eliminate the above requirement. Thenew network structure, called SPP-net, can generate a fixed-length representation regardless of image size/scale. Pyramidpooling is also robust to object deformations. With these advantages, SPP-net should in general improve all CNN-based imageclassification methods.
1 Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun Abstract—Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224 224) input image.This require-
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: