Jul 23, 2025 · These models can detect objects in real-time and with great precision thanks to their robust GPUs and vast annotated datasets. Deep learning is the foundation of contemporary object …

Oct 24, 2025 · In the current AI-centric environment, object detection is a focal point of computer vision applications—be it in autonomous vehicles, surveillance systems, medical imaging, or retail analytics.

Object detection is a technique that uses neural networks to localize and classify objects in images. This computer vision task has a wide range of applications, from medical imaging to self-driving cars. …

Dec 1, 2025 · This review paper starts with a quick overview of object detection followed by traditional and deep learning models for object detection. The section on deep learning models provides a …

Jan 2, 2025 · This comprehensive survey presents an in-depth analysis of the evolution and significant advancements in object detection, emphasizing the critical role of machine learning (ML) and deep …

Modern object detection models use deep learning (usually convolutional neural networks) to extract features from an input image, then predict bounding boxes and class labels for objects. They perform …

cted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable architectures. Their performance easily stagna.

Nov 17, 2023 · Object detection is a subfield of computer vision that focuses on detecting and classifying multiple objects within an image or video. It plays a vital role in a wide range of applications, …

Jun 23, 2025 · Object detection using Deep Learning is a key task in computer vision that allows machines to identify and locate multiple objects within images or video frames.

Oct 4, 2024 · Object detection is an important computer vision task used to detect instances of visual objects of certain classes (for example, humans, animals, cars, or buildings) in digital images such …