Efficient Object Detection with SSD MobileNetV3

Artificial intelligence (AI) has had a significant influence on object detection, a crucial component of computer vision, in recent years. The Single Shot MultiBox Detector (SSD) MobileNetV3 Large Model has been the focus of this work, which highlights its adaptability and efficiency in the multidimensional item recognition area. The paper examines dedicated and generic object detection; architectures such as SSD, Faster R-CNN, and YOLO facilitate the usage of generic object detection. Two techniques used in artificial intelligence are machine learning and deep learning. Various approaches to object identification are explored in the literature. Yolo and EfficientDet with SSD in terms of accuracy have been compared. Cutting edge models are discussed in the article along, with considerations, on data security. Concerns, about privacy and ethical issues related to bias. The analysis of object detection algorithms and findings were revealed in the study. Applications truly showcase the versatility of the SSD MobileNet V2 model involving tasks, like handling devices and navigating through various terrains.