Object Detection Model

Object detection models aim to automatically identify and locate objects within images or videos, a crucial task with broad applications. Current research emphasizes improving model accuracy and efficiency, particularly for challenging scenarios like detecting small or fuzzy objects, and adapting models to diverse data distributions and resource-constrained environments. Popular architectures include YOLO and EfficientDet variants, along with newer approaches leveraging transformers and diffusion models. These advancements are driving progress in fields ranging from autonomous vehicles and industrial automation to medical image analysis and agricultural monitoring.