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Abstract: This article mainly introduces the evaluation indicators of deep learning classification tasks, including basic application, practical skills, principles and mechanisms, hoping to be helpful to you. This article is shared from Huawei cloud community< Common evaluation indicators for deep learning classification tasks >Original ...

introduction Based on PyTorch framework, this paper uses CNN convolutional neural network to realize MNIST handwritten numeral recognition, which runs only on CPU. Four structures, Linear pure Linear layer, CNN convolutional neural network, Inception network and Residual residual network, have been used to recognize handwritten digits fro ...

Reference material: A note of someone's quantification principles https://blog.csdn.net/sinat_31425585/article/details/101607785 Someone's more detailed introduction to int8 https://zhuanlan.zhihu.com/p/58182172 Someone's understanding of ncnn quantification principles and source codes (ncnn quantization is based on tensorRT improvements) https ...

Reprint location: spatial transform network In CNN classification, the locality, translation invariance, reduction invariance and rotation invariance of input samples need to be considered to improve the accuracy of classification. The essence of these invariance is the classical methods of image processing, that is, image clipping, translatio ...

Mobile phone buddies, especially those with little sisters, are now being written out to download B's dance videos. Now, interested friends can try to practice their hands, and then download other areas such as animation, music, fashion, ghost and tiktok, etc. after they master the method, B can help them to learn how to do the work. Download ...

Original link: http://tecdat.cn/?p=25067 This paper describes how to} perform principal component analysis (PCA) using R. You will learn how to} use PCA_ Forecast_ New individual and variable coordinates. We will also provide_ PCA results_ The theory behind it.There are two general methods to perform PCA in R:_ Spectral decomposition_ , check t ...

Recently, I studied the knowledge of artificial intelligence image recognition, using the famous tensorflow tool. At the same time, in order to avoid repeated wheel building, I used the object detection api implemented by Google to realize image recognition. The download address is as follows: https://github.com/tensorflow/models In fact, ther ...

win 10  anaconda  pycharm Project address: https://github.com/matterport/Mask_RCNN 1. Environment configuration Reference https://blog.csdn.net/hesongzefairy/article/details/104702119 2. Data set preparation Create folder dataset The pic folder contains the original pictures Then label the picture with labelme, and save the marked js ...

AI for medical image analysis 1.Data Exploration course code In the first assignment of this lesson, you will use the ChestX-ray8 Data were taken from chest X-ray images. In this notebook, you will have the opportunity to explore this dataset and familiarize yourself with some of the techniques you will use in your first grading assignment B ...

1. Hype-V virtual machine installation openEuler There are many virtual machine platforms, such as vmware, Hype-V, VirtualBox, etc. Considering the compatibility with wsl2, Hype-V is selected here to install the x86 architecture openEuler Turn on the hype-v virtual machine Download the x86 architecture openEuler image Open the openEuler of ...