#YOLO
65 related articles
·3 min
Building a YOLO26 Inference Engine from Scratch in ARM64 Assembly: A Deep Dive into Low-Level Optimization
Deep dive into building a YOLO26n object detection inference engine from scratch using ARM64 assembly and C, covering NEON SIMD, Winograd convolution, GEMM micro-kernels, and cache tiling optimizations.
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·2 min
Ego Vision: A Deep Dive into the YOLO11-Based Driving Action Prediction System
Ego Vision is an open-source autonomous driving perception project integrating YOLO11, ByteTrack, and Depth Anything V2 to predict GO/SLOW DOWN/STOP/EMERGENCY BRAKE actions.
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·2 min
YOLO-Distill: A YOLOv9 Knowledge Distillation Toolkit Under MIT License for Free Commercial Use
YOLO-Distill is an open-source YOLOv9 knowledge distillation toolkit under MIT license, supporting CWD and MGD feature distillation for lightweight edge deployment.
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·3 min
YOLO-Pose Real-Time Yoga Pose Recognition and Correction System Explained
A deep dive into a real-time yoga pose recognition system built with YOLO-Pose: 33 keypoints, deterministic logic engine, and geometric angle thresholds for explainable AI coaching.
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·6 min
Introducing Consistency Regularization to YOLOv8: Principles, Practice, and Performance Trade-offs
An in-depth analysis of introducing consistency regularization into YOLOv8, covering dual-branch augmentation, consistency loss construction, robustness gains, and training cost trade-offs for object detection optimization.
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·4 min
YOLO Learning Roadmap: From Version Evolution to Source Code Deep Dive
A systematic YOLO learning roadmap: from understanding V1/V3/V4 version evolution, to building knowledge via video, to mastering implementation by debugging source code.
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·2 min
RF-DETR Local Deployment Tutorial: A Higher-Accuracy Object Detection Alternative to YOLO
RF-DETR is the first real-time detector to surpass 60 mAP on COCO. This guide covers full local deployment: Conda setup, pip install, and image/video inference.
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·3 min
Industrial Defect Detection: OpenCV vs. YOLO — A Complete Guide to Scenario-Based Decision Making
Compare OpenCV vs. YOLO for industrial defect detection. Analyze selection criteria across data needs, accuracy, deployment, and get learning roadmap advice.
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Tutorials·2 min
Claude Code Three Modes Explained: Auto-Edit, Plan & YOLO Fully Automatic Mode
A detailed guide to Claude Code's three working modes: Auto-Edit (Shift+Tab), Plan mode, and YOLO fully automatic mode — how to enable them, ideal use cases, and key considerations for developers.
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Deep Dives·1 min
The Complete Evolution of YOLO from V1 to V11: A Comprehensive Comparison of Architecture, Accuracy, and Speed
A complete breakdown of YOLO object detection from V1 to V11, covering Anchor Box, multi-scale detection, CSP-Darknet, C2f, and more.
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·3 min
Pothole Detection Model Misclassifying Roadsides? A Practical Guide to Object Detection Optimization
Pothole detection model misclassifying roadsides? Learn systematic approaches to reduce false positives through negative samples, annotation quality, data augmentation, drone small object detection, and segmentation strategies.
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·3 min
AI Game Development Showdown: Claude, Kimi K3, and ChatGPT Recreate Classic Games — Who Wins?
Bilibili creator tests Claude Fable 5, Kimi K3, and ChatGPT Codex recreating Hollow Knight, Cuphead, and Zelda — comparing code quality, collision detection, and Boss design.
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·5 min
Open-Source STEM Education Robot: Smart Ball-Fetching Interaction Powered by Edge AI Object Detection
An open-source STEM education robot using Edge Impulse edge AI for local object detection, teaching kids computer vision and ML through an engaging ball-fetching game with anthropomorphic design.
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·4 min
Choosing the Wrong Agent Ruins Everything: Why the Same Model Can Perform Like Two Completely Different AIs
The same LLM API performs drastically differently under different Agent frameworks. Through a real database crash case, this article analyzes why choosing the right Agent matters more than switching models.
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·1 min
Radxa Cubie A7Z Real-World Test: 330ms End-to-End Object Detection Latency Under Full NPU Load
Deep analysis of Radxa Cubie A7Z achieving 330ms glass-to-glass object detection latency under full NPU load, covering latency breakdown, practical use cases, and edge AI optimization strategies.
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·7 min
DIY Companion Robot: Building Your AI Desktop Buddy with Jetson Orin
A maker builds a DIY companion robot with NVIDIA Jetson Orin and 4S LiPo battery. Explore the full development journey from first power-up to AI interaction, including edge computing, power design, and companion robot trends.
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·2 min
6 High-Paying AI Career Paths: A Beginner's Shortcut and Salary Guide
A breakdown of the 6 best high-paying AI career paths for beginners: LLM application development, AI agents, computer vision, AI infrastructure, AIGC, and embodied AI—with salary ranges, core skills, and who they suit.
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·6 min
AI Application Engineer Interview Guide: Core Topics in Model Quantization and Inference Deployment
A systematic review of must-know topics for AI Application Engineer interviews: PTQ/QAT quantization, operator fusion, inference pipelines, latency/throughput analysis, and edge deployment of detection/segmentation/BEV models.
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·6 min
AI Application Engineer Interview Guide: Core Topics on Model Quantization and Inference Deployment
A systematic guide to must-know AI application engineer interview topics: PTQ/QAT quantization, operator fusion, inference pipelines, latency/throughput analysis, and edge deployment of detection/segmentation/BEV models.
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·7 min
The Complete AI Character LoRA Training Workflow: Hands-On Multi-Character Consistency Generation with Local Deployment
A detailed guide to a complete local AI character generation workflow: from the five golden rules of LoRA training and automated ComfyUI dataset construction to hands-on comparisons of Crea2, Ideogram4, and Wan for multi-character same-frame interaction—all running free on personal hardware.
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