Tiny YOLO

OSDDY: A Small Drone Target Monitoring and Detection System Based on Embedded Systems and Deep YOLO Algorithm

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OSDDY: A Small Drone Target Monitoring and Detection System Based on Embedded Systems and Deep YOLO Algorithm

Click the blue text Follow us Follow and star Never get lost again Computer Vision Research Institute Public Account ID｜Computer Vision Research Institute Learning Group｜Scan the code on the homepage to get the joining method Article link:https://link.springer.com/article/10.1186/s13640-021-00559-1 Column of Computer Vision Institute Computer vision is an interdisciplinary field used for target detection. Target detection is … Read more

Deploying Inference with OpenCV 4.8 and YOLO 11 in C++

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Deploying Inference with OpenCV 4.8 and YOLO 11 in C++

Click the blue text above to follow us WeChat Official Account:OpenCV Academy Follow us for more knowledge on computer vision and deep learning Since the release ofYOLOv5 version 7.0, and the introduction of YOLOv8 and YOLO 11, previous versions of OpenCV 4.6 can no longer load exported ONNX format models. Only OpenCV 4.7 and above … Read more

YOLO v8.3.107 Released! Rockchip RKNN Fixes, OpenVINO Compatibility Upgrades, Enhancing Developer Efficiency!

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YOLO v8.3.107 Released! Rockchip RKNN Fixes, OpenVINO Compatibility Upgrades, Enhancing Developer Efficiency!

📢 Core Update Interpretation 1. Rockchip RKNN Compatibility Fix• Issue Resolved：Fixed the <span>torch_to_mnn</span> file path handling issue, ensuring the stability of model export for Rockchip chips.• User Benefits：RKNN developers will no longer face model deployment failures due to path errors, making deployment on edge devices smoother! 2. OpenVINO and macOS Compatibility Optimization• Version Lock：Limited OpenVINO … Read more

Deployment Practice Test of DeepSeek-R1:7B on Raspberry Pi 5 with Hailo-8L and M2-HAT+

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Deployment Practice Test of DeepSeek-R1:7B on Raspberry Pi 5 with Hailo-8L and M2-HAT+

I have recently been deeply involved in the research and development of LLM/SLM (Large Language Models/Small Language Models), covering areas such as agent development, RAG-enhanced retrieval, fine-tuning, model distillation, and MLOps. To expand the technical boundaries, I have simultaneously explored the field of edge AI, focusing on deployment practices on the Raspberry Pi 5 (equipped … Read more

DAC 2019 Low Power Object Detection System Design Challenge: GPU and FPGA Dual Championship Solutions Explained

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DAC 2019 Low Power Object Detection System Design Challenge: GPU and FPGA Dual Championship Solutions Explained

Machine Heart Released Author: Zhang Xiaofan On June 5, 2019, the second “Low Power Object Detection System Design Challenge” hosted by the top electronic automation design conference DAC concluded in Las Vegas (Machine Heart reported on the first competition last year). This competition aimed to design high-precision and energy-efficient object detection systems for terminal devices, … Read more

Innovations in the Post-Moore Era: Implementing Tiny YOLO V4 on MYIR FPGA to Empower AIoT Applications

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Innovations in the Post-Moore Era: Implementing Tiny YOLO V4 on MYIR FPGA to Empower AIoT Applications

Dec. Follow us by clicking the blue text 2024.12 Tip: Learn how to deploy Tiny YOLO v4 on MYIR’s ZU3EG FPGA development board, comparing the performance of FPGA, GPU, and CPU to assist AIoT edge computing applications. 1. Why choose FPGA: Addressing 7nm process and AI limitations In the context of global semiconductor process restrictions … Read more