Jan 1, 2023 · This review paper starts with a quick overview of object detection followed by object detection frameworks, backbone convolutional neural network, and an overview of common datasets along with the evaluation metrics.

Jan 26, 2021 · Object recognition is refers to a collection of related tasks for identifying objects in digital photographs. Region-Based Convolutional Neural Networks, or R-CNNs, are a family of techniques for addressing object localization and recognition …

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 comprehensive overview of one-stage and two-stage object detectors. ... This feature vector can then be used as an input to machine learning algorithms for ...

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 as photos or video frames.

Object detection is a cornerstone of computer vision, focusing on the precise identification and localization of objects within images and videos. This sophisticated technology is fundamental to a wide array of applications across multiple industries.

Object recognition, a subfield of computer vision, focuses on the ability to detect, analyze, and classify specific objects within images and videos.

Abstract: This article provides an overview of object detection and its significance in various applications. Object detection, a process that detects images of visual objects, encompasses tasks such as number plate recognition, face detection, text detection, and pedestrian detection.

Sep 29, 2023 · Object detection is a profound computer vision technique that identifies and labels objects within images, videos, and even live footage. Models that perform object detection are trained with a surplus of annotated visuals in order to carry out this process with new data.

Apr 28, 2025 · This systematic review deconstructs object detection research's evolution, methodology, and challenges by integrating evidence from high-impact repositories. Publication trends, dataset usage, and domination of leading venues like CVPR and ICCV in driving the field are addressed. Comparative performance assessment of YOLO, Faster R-CNN, and DETR considers their performance, scalability, and ...

Jan 27, 2024 · Using object detection, a fundamental computer vision task, has revolutionized how machines interpret the visual world. Unlike image classification, where the objective is to classify an entire image, object detection can be used to identify and locate objects within an image or video frame (which is the same as a image / picture).