Yes-Net: An effective Detector Based on Global Information

28 Jun 2017 Liangzhuang Ma Xin Kan Qianjiang Xiao Wenlong Liu Peiqin Sun

This paper introduces a new real-time object detection approach named Yes-Net. It realizes the prediction of bounding boxes and class via single neural network like YOLOv2 and SSD, but owns more efficient and outstanding features... (read more)

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Methods used in the Paper


METHOD TYPE
Average Pooling
Pooling Operations
Global Average Pooling
Pooling Operations
Batch Normalization
Normalization
Max Pooling
Pooling Operations
Softmax
Output Functions
Convolution
Convolutions
Darknet-19
Convolutional Neural Networks
Non Maximum Suppression
Proposal Filtering
1x1 Convolution
Convolutions
SSD
Object Detection Models
YOLOv2
Object Detection Models