Object detection is one of the most important challenges in computer vision. Deep learning-based solutions can solve it very effectively. To solve any problem using deep learning, first, we need to ...
Small object detection refers to the task of identifying and localizing objects that are relatively small in size within digital images. These objects typically have limited spatial extent and low ...
Face recognition models: This article focuses on the comprehensive examination of existing face recognition models, toolkits, datasets and FR pipelines. From early Eigen faces and Fisher face methods ...
YOLO-NAS is currently the latest YOLO object detection model. From the outset, it beats all other YOLO models in terms of accuracy. The pretrained YOLO-NAS models detect more objects with better ...
Image segmentation is a core vision problem that can provide a solution for a large number of use cases. Starting from medical imaging to analyzing traffic, it has immense potential. Instance ...
Developing a new YOLO-based architecture can redefine state-of-the-art (SOTA) object detection by addressing the existing limitations and incorporating recent advancements in deep learning. Deep ...
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