There are some details of reading and implementing the Network In Network for image classification.
There are some details of reading and implementing the Network In Network for image classification.
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CRNet(Cross-Reference Networks)[1] make predictions for both the support image and the query image. It can better find the co-occurrent objects in the
FSL-Survey[1] is a survey on Few-Shot Learning(FSL), which cotains 166 paper to review Few-Shot Learning. They categorize FSL methods from three persp
There are the list of typical Image Classification CNNs. Todos LeNet-5: [ , 1, 32, 32] - [6, 16, 120, 84, 10] AlexNet v1/v2: [ , 3, 224, 224] - [64, 1
FFT(Flow-Fuse Tracker)[1] is an end-to-end DNN tracking approach, that jointly learns both target motions and associations for MOT(multiple object tra
DeepSORT[1] integrates appearance information to improve the performance of SORT, learned a deep association metric. There are some details of reading
A Master of Chongqing University A Computer Vision Practicer Keep Moving