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Source channel @githubtrending · Post #14949 · Jul 12

#jupyter_notebook#darknet#pytorch#scaled_yolov4#yolor#yolov3#yolov4#yolov7 YOLOv7 is a powerful tool for detecting objects in images and videos. It is fast, accurate, and can work well on devices with limited power, making it useful for real-time applications like self-driving cars and surveillance systems. YOLOv7 uses advanced techniques like Feature Pyramid Networks to detect objects of different sizes and can handle complex scenes with overlapping objects. This makes it beneficial for users who need quick and precise object detection in various environments. https://github.com/WongKinYiu/yolov7

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DOFH - DevOps from hell

@dofh_ru · Post #3570 · 02/05/2025, 05:54 PM

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Here we go again! SEV-SNP is vulnerable, again. New AMD SEV-SNP vulnerability: https://github.com/google/security-research/security/advisories/GHSA-4xq7-4mgh-gp6w Exploit: https://github.com/google/security-research/tree/master/pocs/cpus/entrysign Reports about two recent vulnerabilities in SEV-SNP memory encryption and isolation mechanism, on CPU pipeline, cache and branch prediction level: https://www.amd.com/en/resources/product-security/bulletin/amd-sb-3019.html https://www.amd.com/en/resources/product-security/bulletin/amd-sb-3010.html AMD reported that previous approaches to Spectre class attacks will work to fix new vulnerabilities: https://www.amd.com/content/dam/amd/en/documents/epyc-technical-docs/tuning-guides/software-techniques-for-managing-speculation.pdf #cVM #TEE #SEV #SNP #SEV_SNP #AMD

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