基于机器视觉的学园偶像大师自动化脚本
Wearable blind navigation assistant: Raspberry Pi 4 + RealSense D435 + YOLO26n, depth tracking, ego-motion compensation, and local audio/TTS alerts.
Low-profile wearable device to provide the visually impaired with an intuitive "synthetic audio-vision" system for enhanced navigation
CARLA-based emergency vehicle detection and traffic light preemption using YOLOv26n, multi-camera infrastructure sensing, and realistic weather-diverse data collection.
Classification of skin lesions (among 7 classes) using the file https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/DBW86T and the Yolo26 model.
Ultralytics YOLO26n 在树莓派4B 上的基准测试 | Ultralytics YOLO26n on Raspberry Pi 4B Benchmark
YOLO 26 Segmentation Fine-tuning pipeline.
Traffic Sign Recognition (TSR) vison model for Advanced Driver Assitance System (ADAS) using YOLO-based object detection, trained on a custom Indian traffic sign dataset aligned with Indian Road Congress (IRC:67-2022) standards.
A tool for automatically tracking FRC robots from match footage
Real-Time Road Anomaly Detection from Dashcam Footage on Raspberry Pi
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