For engineers, researchers, and product teams building real-time vision systems—whether for surveillance cameras, autonomous drones, or mobile apps—achieving high detection…
Edge AI
RFBNet: High-Accuracy, Real-Time Object Detection Without Heavy Backbones 1422
When building real-world computer vision systems—whether for autonomous drones, industrial inspection, or mobile apps—one of the toughest trade-offs is between…
YOLOv6: Real-Time Object Detection Optimized for Speed, Accuracy, and Industrial Deployment 5869
YOLOv6 is a high-performance, single-stage object detection framework developed by Meituan with a strong emphasis on real-world industrial applications. Unlike…
GhostNet: High-Accuracy Vision Models with Minimal Compute for Edge Deployment 4355
Overview Deploying powerful computer vision models on resource-constrained devices—such as smartphones, IoT sensors, or drones—has long been a major engineering…
PP-PicoDet: Real-Time Object Detection with SOTA Accuracy on Mobile and Edge Devices 13974
In today’s era of intelligent edge computing, deploying high-performance computer vision models on resource-constrained devices like smartphones, embedded sensors, and…
Mini-InternVL: Achieve 90% of Multimodal Performance with Just 5% of Model Size for Edge and Consumer Deployments 9328
In an era where multimodal large language models (MLLMs) are rapidly advancing, a critical barrier remains: most high-performing vision-language models…
Parallax: Run LLMs on Decentralized Devices Without Costly GPU Clusters 1004
Deploying large language models (LLMs) today often means relying on expensive, centralized infrastructure—specialized GPU clusters, high-bandwidth data centers, and recurring…