adversarial examples

Practical Guide to PyTorch Training Acceleration Techniques

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Practical Guide to PyTorch Training Acceleration Techniques

Introduction This article discusses how to apply torch for mixed precision computation, data parallelism, and distributed computing. Author丨Not Important What Name @ Zhihu Link丨https://zhuanlan.zhihu.com/p/360697168 Due to recent programs requiring high speed, I wanted to get results quickly, so I specifically learned about mixed precision computation and parallel operations. Since there are already many articles explaining … Read more

Tips for Upgrading to PyTorch 2.0

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Tips for Upgrading to PyTorch 2.0

Source: DeepHub IMBA This article is about 6400 words long and is recommended for a 12-minute read. In this article, we will demonstrate the use of new features in PyTorch 2.0 and highlight some issues you might encounter when using it. It has been some time since the release of PyTorch 2.0. Have you started … Read more

Research on Few-Shot Class-Incremental Recognition Technology for SAR Images

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Research on Few-Shot Class-Incremental Recognition Technology for SAR Images

Click the blue “Radar Journal” to follow From October 22 to October 30, 2023, the 3rd Radar Journal Doctoral Forum was successfully held! Doctoral student Zhao Yan from National University of Defense Technology presented an academic report titled “Research on Few-Shot Class-Incremental Recognition Technology for SAR Images” at the SAR Image Interpretation Technology Sub-Forum on … Read more

AI Image Recognition Meets Adversarial Images

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AI Image Recognition Meets Adversarial Images

Click the above “Beginner Learning Vision” to choose to add “Star” or “Top” Important content delivered immediately 【Guide】How big is the gap between AI and human vision? Researchers from UC Berkeley and other universities created a dataset of 7,500 “natural adversarial examples”. After testing many machine vision systems, they found that AI’s accuracy dropped by … Read more

Deep Learning and SAR Applications

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Deep Learning and SAR Applications

Click on the blue text above the image “Smart World” to subscribe Introduction Although it seems that the hype curve of deep learning has somewhat contracted (at this stage, the technology is still not mature, and the products are not yet refined, but the market has already heated up, and people’s expectations are very high.) … Read more

First Published Foundation Model for SAR Image Target Recognition

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First Published Foundation Model for SAR Image Target Recognition

Machine Heart released Machine Heart Editorial Department Synthetic Aperture Radar (SAR) is an active detection technology based on electromagnetic waves, providing all-weather, all-time ground observation capabilities. It has developed into an indispensable tool for ground observation, with significant applications in both military and civilian fields. Automatic Target Recognition (ATR) is the core issue of intelligent … Read more

17 Methods To Speed Up PyTorch Training

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17 Methods To Speed Up PyTorch Training

Selected from efficientdl.com Author: LORENZ KUHN Translated by: Machine Heart Editor: Chen Ping Master these 17 methods to accelerate your PyTorch deep learning training with minimal effort. Recently, a post on Reddit gained immense popularity. The topic was about how to speed up PyTorch training. The original author is LORENZ KUHN, a master’s student in … Read more

Guide to Fooling Neural Networks: How to Trick Deep Learning Models

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Guide to Fooling Neural Networks: How to Trick Deep Learning Models

This is a work by Big Data Digest, please refer to the end of the article for reproduction requirements. Original Author | Adam Geitgey Translation | Wu Shuang, Da Li, Da Jieqiong, Aileen To know oneself and one’s enemy, whether you want to become a hacker (which is not recommended!) or prevent future hacking intrusions, … Read more