Reread target detection -- ssd

[target detection – R-CNN, Fast R-CNN, Fast R-CNN] https://www.cnblogs.com/yanghailin/p/14767995.html [target detection SSD] https://www.cnblogs.com/yanghailin/p/14769384.html [detailed explanation of anchor generation of ssd] https://www.cnblogs.com/yanghailin/p/14868575.html [detailed explanation of ssd network] https://www.cnblogs.com/ ...

Added by oskom on Fri, 17 Sep 2021 16:44:18 +0300

Visualizing models, data, and training using tensorboard

abstract In order to understand what happened, we printed out some statistics during model training to see whether the training was in progress. However, we can do better: PyTorch is integrated with TensorBoard, which is a tool for visualizing the results of neural network training. This tutorial explains some of its functions using the fa ...

Added by p0pb0b on Fri, 17 Sep 2021 06:26:32 +0300

TensorFlow by Google CNN machine learning foundations: EP #5 - classifying real world images

The picture classification structure is convenient for training and testing 1. Use convolution for complex images https://bit.ly/tfw-lab5 #@title Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apac ...

Added by php_guest on Fri, 10 Sep 2021 03:19:16 +0300

pytorch | Dragon Boat Festival learning notes

pytorch learning import torch import numpy as np a=torch.rand(4,3,28,28) #torch.rand(batch_size, channel, row, column) a[0].shape #batch_ shape with size = 0: torch.Size([3, 28, 28]) a[0,0].shape #batch_ shape with size = 0 and channel 0: torch.Size([28, 28]) a[0,0,2,4] #batch_size=0, pixels in Row 2 and column 4 on the 0 ...

Added by tacojohn on Sat, 04 Sep 2021 02:45:12 +0300