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🔱 Hello, I'm 👉 Classmate K，100 cases of deep learning The series will be updated continuously. Welcome to like 👍, Collection ⭐, follow 👀 This paper will use GAN model to realize the generation of handwritten digits, focusing on understanding the structure and construction method of GAN model. 1, Preliminary work 🚀 My environme ...

1. Introduction of BP algorithm 1.1 Background Enlightened by the neural network in the human brain, computer simulation of the neural network in the human brain is used to realize machine learning technology of artificial intelligence. The bp algorithm is the most successful neural network algorithm to date. The bp algorithm can be used ...

Where is the video memory used? Generally, when training neural networks, the memory is mainly occupied by network models and intermediate variables. The parameters of convolution layer, full connection layer and standardization layer in the network model occupy the video memory, while the activation layer and pooling layer do not occupy ...

Gated Channel Transformation for Visual Recognition (GCT) This article is a reproduction of an Attention article invested by Baidu & Syndney in CVPR2020. It proposes a general and lightweight change unit, which combines normalization method and Attention mechanism, which is easy to analyze the relationship between channels (competition or ...

This article is my recent self-study pytorch notes, according to Introduction to pytorch Basics Please correct any mistakes or misunderstandings in the notes of what you have learned. The feelings and experiences of this teaching video are at the end of the article. Love the official account if you like. Some of your learning experience and rec ...

Thesis Name: segnet: a deep revolutionary encoder decoder architecture for image Segmentation Paper link: SegNet Project address: Segnet Cafe version Motivation 1. Deep learning needs to extract the high-order semantic features of the image and needs continuous down sampling. Continuous down sampling will lead to the loss of image boundary in ...

GOAL: to train a model on a variety of learning tasks, such that it can solve new learning tasks using only a small number of training samples. Introduction: starting from face recognition, if a company has 50 people, it needs to make a face recognition system. According to the traditional deep learning idea, the recognition results should b ...

Source: Hengyuan cloud community( Hengyuan zhixiangyun)Original address| histogramOriginal author | insterLearning objectivesMaster the histogram calculation and display of imagesUnderstand mask applicationsFamiliar with histogram equalization and adaptive equalization1 gray histogram1.1 principleHistogram is a method of data statistics, and or ...

Related articles 1, Python getting started environment configuration: Anaconda3 and pycharm installation tutorial 2, labelimg application: dataset Tags 3, Build a pytoch environment under Windows (CPU version) 4, Building a pytoch environment under Windows (super detailed) 1, YOLOV5 environment construction (official requirements: ...

Abstract: This article will explain in detail Keras's implementation of classical deep learning text classification algorithms, including LSTM, BiLSTM, BiLSTM+Attention, CNN and TextCNN. This article is shared from Huawei cloud community< Keras deep learning Chinese text classification ten thousand word summary (CNN, TextCNN, BiLSTM, attenti ...