Adaptive Object Detection with ESRGAN-Enhanced Resolution & Faster R-CNN

• URL: http://arxiv.org/abs/2506.11122v1
• Date: Tue, 10 Jun 2025 05:49:54 GMT
• Title: Adaptive Object Detection with ESRGAN-Enhanced Resolution & Faster R-CNN
• Authors: Divya Swetha K, Ziaul Haque Choudhury, Hemanta Kumar Bhuyan, Biswajit Brahma, Nilayam Kumar Kamila,
• Abstract summary: Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN) and Faster Region-Convolutional Neural Network (Faster R-CNN) are proposed.<n>ESRGAN enhances low-quality images, restoring details and improving clarity.<n>Faster R-CNN performs accurate object detection on the enhanced images.
• Score: 1.3107174618549584
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this study, proposes a method for improved object detection from the low-resolution images by integrating Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN) and Faster Region-Convolutional Neural Network (Faster R-CNN). ESRGAN enhances low-quality images, restoring details and improving clarity, while Faster R-CNN performs accurate object detection on the enhanced images. The combination of these techniques ensures better detection performance, even with poor-quality inputs, offering an effective solution for applications where image resolution is in consistent. ESRGAN is employed as a pre-processing step to enhance the low-resolution input image, effectively restoring lost details and improving overall image quality. Subsequently, the enhanced image is fed into the Faster R-CNN model for accurate object detection and localization. Experimental results demonstrate that this integrated approach yields superior performance compared to traditional methods applied directly to low-resolution images. The proposed framework provides a promising solution for applications where image quality is variable or limited, enabling more robust and reliable object detection in challenging scenarios. It achieves a balance between improved image quality and efficient object detection

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