ODConv dynamic convolution module ODConv can be regarded as a continuation of CondConv, which expands the dynamic characteristics of CondConv in one dimension and takes into account the dynamics of airspace, input channels, output channels, etc., so it is called full-dimensional dynamic convolution. ODConv adopts a multi-dimensional attention mechanism through a parallel strategy to learn […]
Tag: convolution
P18 Neural Network Special Topic-Convolutional Layer
Read the document again inchannel input channel number outchannel number of output channels (number of convolution kernels) kernel_size convolution kernel size stride=1 convolution process path size padding Whether padding is performed during the convolution process dilation The corresponding bit distance in the convolution kernel groups group convolution is generally 1 bias bias is generally True […]
SAConv convolution implemented in pytorch code
SAConv convolution The SAConv convolution module is a “plug-and-play” convolution with higher accuracy and faster speed. Currently, many methods have been proposed to reduce model redundancy and accelerate model inference speed. However, these methods often focus on eliminating unimportant filters or build efficient computing units, but ignore the pattern redundancy within the features. Original address: […]
Convolutional network: Recognizing handwritten digits with an accuracy of 97.3% after 50 rounds
Convolutional network: achieving 50 rounds of accuracy in recognizing handwritten digits 1 Import necessary libraries 2 torchvision has built-in commonly used data sets and the most common models 3 Data batch loading 4 drawing examples 5 Create the model 7 Set whether to use GPU 8 Set up the loss function and optimizer 9 Define […]
Python implements a malicious code classification system based on convolutional neural network
Resource download address: https://download.csdn.net/download/sheziqiong/88324878 Resource download address: https://download.csdn.net/download/sheziqiong/88324878 Main idea At present, there are generally few classification studies on malicious code images in the field of malicious code. Therefore, this article uses the disassembled machine code files of malicious code samples to improve the B2M algorithm to generate square malicious code images with the same […]
Sentiment analysis through convolutional neural network
Author: Zen and the Art of Computer Programming 1. Introduction Overview Sentiment Analysis is an important task in the field of natural language processing. In the Internet era, sentiment analysis has become a key link that affects user experience, marketing effectiveness and many other aspects. Sentiment analysis of text data can help companies understand consumers’ […]
[Popular understanding] CNN convolutional neural network – with scene examples
1. Overview of CNN algorithm The full name of CNN is Convolutional Neural Networks, ConvNets, which is called convolutional neural network and is one of the classic algorithms of deep learning. CNN is generally used for image classification, retrieval, face recognition, target positioning, etc. In the process of conventional image processing, there are the following […]
Fruit and vegetable recognition system Python+Django+TensorFlow+convolutional neural network algorithm
The fruit and vegetable recognition system uses Python as the main development language and builds a convolutional neural network algorithm based on the deep learning TensorFlow framework. And by training the data set, a model with higher recognition accuracy is finally obtained. Based on the Django framework, a web-based operating platform is developed to allow […]
Convolutional neural network realizes Hollywood star recognition – P6
This article isThe learning record blog in the 365-day deep learning training camp Reference article: Pytorch in action | Week P6: Hollywood star identification Original author: Classmate K | Tutoring, project customization Article source: Student K’s study circle Directory environment step Environment settings package reference Define a global device object data preparation Define the directory […]
[YoloV5 modification] Yolov5 modification based on GnConv convolution module
HorNet paper address: https://arxiv.org/pdf/2207.14284.pdf HorNet is a new network structure module based on the Swin transformer structure and combined with the idea of large core. Using this module, the author achieved SOTA results in classification, segmentation and detection tasks on the ImageNet-1k data set at the time. It is an improvement idea that can effectively […]