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 …

Jan 26, 2021 · Object detection is more challenging and combines these two tasks and draws a bounding box around each object of interest in the image and assigns them a class label. Together, …

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. …

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.

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 …

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

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 …

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 …

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 …