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 ...
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Exploring SAHI: Slicing Aided Hyper Inference for Small Object Detection
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: Advancements, Toolkit, and Datasets
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 ...
Train YOLO NAS on Custom Dataset
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 ...
Train YOLOv8 Instance Segmentation on Custom Data
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 ...
Meet YOLO-NAS: New YOLO Object Detection Model Beats YOLOv6 & YOLOv8
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 ...
