Programming VIP

Pytoch: image style migration Copyright: Jingmin Wei, Pattern Recognition and Intelligent System, School of Artificial and Intelligence, Huazhong University of Science and Technology Reference Image Style Transfer Using Convolutional Neural Networks A Neural Algorithm of Artistic Style Perceptual Losses for Real-Time Style Transfer a ...

Pytorch: Target Detection-Feature Pyramid-FPN Copyright: Jingmin Wei, Pattern Recognition and Intelligent System, School of Artificial and Intelligence, Huazhong University of Science and Technology Pytorch Tutorial Column Link This tutorial is not commercial and is only for learning and reference exchange. If you need to reproduce it, ...

MNIST dataset MNIST dataset is already a "chewed" dataset. Many tutorials will "start" on it and almost become a "model" However, some people may not know it very well. Let's introduce it MNIST datasets are available in http://yann.lecun.com/exdb/mnist/ Get, which consists of four parts: Training set images: ...

1, Preliminary work My environment: Locale: Python 3 six point fiveCompiler: Jupiter notebookDeep learning environment: tensorflow2 four point oneData address: [portal] Previous highlights: 100 cases of deep learning convolutional neural network (CNN) to realize mnist handwritten numeral recognition | day 1100 cases of deep learning - c ...

Ptorch cifar10 image classification LeNet5 Here is a summary: Summary 4. Define network (LeNet5) Handwritten font recognition model LeNet5 was born in 1994 and is one of the earliest convolutional neural networks. Through ingenious design, LeNet5 uses convolution, parameter sharing, pooling and other operations to extract features, avoid ...

The three neural networks described above are "series", just the continuous stacking of convolution layers, and the structure is relatively simple. The next two blogs will introduce the "parallel" structure in GoogLeNet and ResNet, which are also the last two neural networks to be introduced before officially entering the ta ...

I. Introduction Problem: Existing CNN s require fixed-size input pictures, which can be achieved by clipping or distorting the original image. These two methods may have different problems: (i) The clipped area may not contain the whole object; (ii) The distortion operation results in unnecessary geometric distortion of the target. If the targ ...

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 ...

🔱 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 the concept V3 model to realize sign language recognition, focusing on understanding the structure and construction method of the concept V3 model. 1, Preliminary work My enviro ...