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 …

Dec 1, 2025 · Comparative analysis of object detection algorithms based on strengths and weaknesses, the best object detection methods for different applications are discussed and highlight the metrics …

Aug 19, 2025 · Object detection has grown from rudimentary edge detection algorithms to sophisticated deep learning models. Here’s a consolidated overview of object detection challenges and the …

Apr 15, 2024 · A guide on object detection algorithms and libraries that covers use cases, technical details, and offers a look into modern applications.

Methods for object detection generally fall into either neural network-based or non-neural approaches. For non-neural approaches, it becomes necessary to first define features using one of the methods …

Feb 18, 2025 · Object detection is a computer vision technique that identifies and locates different types of objects in an image or video. Unlike image classification, which only assigns labels, this method …

Oct 4, 2024 · Popular algorithms used to perform object detection include convolutional neural networks (R-CNN, Region-Based Convolutional Neural Networks), Fast R-CNN, and YOLO (You Only Look …

Jan 2, 2025 · We explore a wide spectrum of methodologies, ranging from traditional approaches to the latest DL models, thoroughly evaluating their performance, strengths, and limitations.

Jun 11, 2025 · Traditional object detection techniques rely on handcrafted features and rule-based approaches. These methods can be broadly categorized into two main streams: edge detection and …

Feb 5, 2024 · An in-depth guide explaining object detection algorithms and popular libraries covering real-time examples, technical aspects and limitations.