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Learn how to build an object detection system that locates and classifies dice using CNN-based feature extraction, bounding box regression…Continue reading on Medium »
In our previous blog post in this series, we discussed state-of-the-art models for object detection: the architectures, the theory, and what makes YOLO12, YOLO26, and RF-DETR tick....
This article describes how a YOLO-based model can be extended to detect both standard object classes and previously unseen or user-defined objects without retraining the model spec...
Мы собрали модель, которая одновременно решает детекцию, классификацию и сегментацию, и при этом остается радикально легче и экономичнее по ресурсам, чем любые современные SOTA‑арх...
Comparing YOLOv9, YOLOv10, YOLOv11, Faster R-CNN MobileNet, and Faster R-CNN EfficientNet to find a model that is not only accurate, but…Continue reading on Medium »
In Advanced Driver Assistance Systems (ADAS), semantic segmentation is one of the most important computer vision technologies. Unlike traditional object detection, which only ident...
Fruit detection in real agricultural environments has long been one of the most stubborn problems in computer vision, and a new study from researchers at the University of Lincoln...
Китайская компания Robbyant представила систему компьютерного зрения LingBot-Depth 2.0, которая помогает роботам точнее ориентироваться в пространстве. Технология решает проблему в...
Every AR toolkit (ARKit, ARCore, RoomPlan, Polycam) bundles SLAM, object detection, and a UI into one closed, heavyweight package. If you just want the middle piece — turn a stream...
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