Object Detection
This blog goes through the architecture of DETR
YOLO11 is here! Continuing the legacy of the YOLO series, YOLO11 sets new standards in speed and efficiency. With enhanced architecture and multi-task capabilities, it outperforms previous models, making it
This research article explains a data-centric fine-tuning approach using YOLOv10 models for kidney stone detection.
YOLOv10 introduces a dual-head architecture for NMS-free training and efficiency-accuracy driven model design. It combines one-to-one and one-to-many label assignments to improve performance without extra computation. YOLOv10 uses lightweight classification
This research article discusses about how data preparation matters for Fine-tuning Faster R-CNN on aerial small object detection.
This article will help you to quickly build and showcase your own deep learning models, using Gradio and OpenCV's DNN module.
