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[2602.15926] A Study on Real-time Object Detection using Deep Learning
Summary
This article explores real-time object detection using deep learning, detailing various algorithms, applications, and future research directions.
Why It Matters
Real-time object detection is crucial across multiple domains, including security, healthcare, and AR/VR. Understanding the advancements in deep learning algorithms can enhance decision-making processes in these areas, making this research highly relevant for developers and researchers in AI and computer vision.
Key Takeaways
- Deep learning algorithms like YOLO and Mask R-CNN significantly enhance object detection accuracy.
- Real-time applications span various fields, including security, healthcare, and navigation.
- The article compares different object detection models and their effectiveness.
- Open benchmark datasets are essential for evaluating object detection models.
- Future research should focus on overcoming current challenges in object recognition.
Computer Science > Computer Vision and Pattern Recognition arXiv:2602.15926 (cs) [Submitted on 17 Feb 2026] Title:A Study on Real-time Object Detection using Deep Learning Authors:Ankita Bose, Jayasravani Bhumireddy, Naveen N View a PDF of the paper titled A Study on Real-time Object Detection using Deep Learning, by Ankita Bose and 2 other authors View PDF HTML (experimental) Abstract:Object detection has compelling applications over a range of domains, including human-computer interfaces, security and video surveillance, navigation and road traffic monitoring, transportation systems, industrial automation healthcare, the world of Augmented Reality (AR) and Virtual Reality (VR), environment monitoring and activity identification. Applications of real time object detection in all these areas provide dynamic analysis of the visual information that helps in immediate decision making. Furthermore, advanced deep learning algorithms leverage the progress in the field of object detection providing more accurate and efficient solutions. There are some outstanding deep learning algorithms for object detection which includes, Faster R CNN(Region-based Convolutional Neural Network),Mask R-CNN, Cascade R-CNN, YOLO (You Only Look Once), SSD (Single Shot Multibox Detector), RetinaNet etc. This article goes into great detail on how deep learning algorithms are used to enhance real time object recognition. It provides information on the different object detection models available, open b...
