Comparative Analysis of Region-Based and Regression-Based Object Detection Techniques using Deep Learning |
Author(s): |
| Kamble Ujjwala Gunvant , TPCTs College of Engineering, Dharashiv.; Dr. Sushilkumar N. Holambe, TPCTs College of Engineering, Dharashiv. |
Keywords: |
| Object Detection, CNN, R-CNN, YOLO, SSD, Deep Learning |
Abstract |
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Object detection is one of the most important tasks in computer vision, where the goal is not only to recognize objects but also to locate them accurately in an image. With the growth of deep learning, especially convolutional neural networks, detection performance has improved significantly. In this work, different approaches such as region-based models (R-CNN family) and regression-based models (YOLO, SSD) are studied and compared. The comparison is done on the basis of speed, accuracy, and computational requirements. It is observed that region-based approaches are more precise, whereas regression-based methods are more suitable for real-time systems. |
Other Details |
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Paper ID: IJSRDV14I20032 Published in: Volume : 14, Issue : 2 Publication Date: 01/05/2026 Page(s): 48-49 |
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