As a network focusing on edge platform deployment, especially for CPU devices, NanoDet naturally chose to use a lightweight backbone network with deep separable convolution.
Here we mainly introduce the default Backbone: GhostNet , this is a lightweight backbone network proposed by Huawei. For details about ...
Posted by hammerslane on Sat, 05 Mar 2022 12:41:03 +0100
Pytorch: Overview of target detection networks, indicator calculation and use of pre-training networks
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 lear ...
Posted by Lyleyboy on Wed, 16 Feb 2022 18:11:43 +0100
The data used in this example is three categories of English data. torchtext is used to process the data, build an iterator and build textcnn. The data is trained with textcnn to get the training results. In this example, the validation set is not used to evaluate the model.
1, Development environment and data set
1. Development envir ...
Posted by nsantos on Sun, 30 Jan 2022 03:55:10 +0100
DenseNet, a densely connected convolution network with Pytorch Note32
A summary of all notes:
Pytorch Note Happy Planet
Previous Resnet enhanced the information flow between the front and back layers through Shortcuts, alleviated the disappearance of gradients to some extent, and built the neural network very deeply. Furthermore ...
Posted by utpal on Mon, 10 Jan 2022 19:21:24 +0100
Convolutional neural network series
In this article, we use a custom implemented LeNet-5 neural network architecture to perform image classification on MNIST data sets.
LeNet was founded in 1998 by Yann Lecun, Leon bottom, yoshua bengio, and Patrick Haffner My thesis Gradient-Based Learning Applied To ...
Posted by lancey10 on Thu, 23 Dec 2021 03:22:48 +0100