Programmer Think

For convolution formula Maybe some people know, maybe some people don't know, or just know but don't understand. But whether you know the meaning of this formula or not, it doesn't affect you to realize a convolution. I won't talk about his specific mathematical meaning first, because many people speak more clearly and thoroughly than I do. Wh ...

PyTorch multi card distributed training DistributedDataParallel catalogue PyTorch multi card distributed training DistributedDataParallel 1.DP mode and DP mode (1) Single process multi GPU training mode: DP mode (2) Multi process multi GPU training mode: DDP mode 2. Pytoch distributed training method 3. Python base trainer (PBT) distribu ...

abstract This example extracts some data from the plant seedling data set as the data set. The data set has 12 categories. It demonstrates how to use the mobile netv3 image classification model of pytorch version to realize the classification task. Through this article, you can learn: 1. How to download from torchvision Models call mobil ...

7. Image outline 7.1 what is image contour Image outline is a curve of continuous points with the same color or gray scale Contour is very useful in shape analysis and object detection and recognition. Function of contour: For graphic analysisObject recognition and detection Note: In order to improve the accuracy of detection, it is neces ...

Alex's alexnet network structure model won the championship in Imagenet 2012 image classification challenge. When training alexnet, the author cycled the training set of 1.2 million images for 90 times, and spent five to six days on two NVIDIA GTX 580 3gb GPUs. Source paper: Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet cl ...

Summary This is a series of pytorch notes that follow station b. There are a lot of classified articles about renet model image recognition on the internet, but the image part is usually just a link to it. Or read a well-known article and prepared the dataset from scratch. One dataset preparation The dataset consists of 102 categories of flo ...

Early Stopping Brief Introduction When we train deep learning neural networks, we usually hope to obtain the best generalization performance. However, all standard deep learning neural network structures such as MLP are easy to over fit: when the error rate of the network in the training set is getting lower and lower, in fact, at a certa ...

Multilayer perceptron Both linear regression and softmax regression are single-layer neural networks. However, deep learning mainly focuses on multi-layer models. Taking multilayer perceptron (MLP) as an example, the concept of multilayer neural network is introduced. Hidden layer Multilayer perceptron introduces one or more hidden layer ...

catalogue Chapter 6 learning related skills 6.1 parameter update 6.1.1 explorer's story 6.1.2 SGD 6.1.3 disadvantages of SGD 6.1.4 Momentum 6.1.5 AdaGrad 6.1.6 Adam 6.1.7 which update method to use 6.1.8 comparison of update methods based on MNIST dataset 6.2 initial value of weight 6.2.1 can the initial value of weight be set to 0 ...

Training data generation Detailed step reference Modification of configuration file This article takes the human hand detection as an example (there is only one label: hand) Add or modify data / hand Names file, which records labels, one label per line (Note: labels corresponding to training data)Add or modify CFG / hand Data file, the cont ...