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Published in International Conference on Computer Vision and Image Processing (CVIP - 2023), 2023
Manas Kagde, Priyanka Choudhary, Rishi Joshi and Somnath Dey
This paper addresses the challenge of recognizing traffic signs in poor visibility, blurriness, and adverse conditions. It employs a two-step approach: enhancing images with a modified MIRNet model and then recognizing signs using the YOLOv4 model to improve recognition accuracy under difficult conditions.
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Published in IEEE 101st Vehicular Technology Conference (VTC2025-Spring), Oslo, 2025
Priyanka Choudhary and Somnath Dey
This paper proposes a novel feature-based Generative Adversarial Network (GAN) to regenerate occluded traffic signs to improve detection accuracy. The GAN-generated features are fused with the Faster R-CNN-generated features. The architecture of GAN is tiny and integrated at the feature level within Faster R-CNN to minimize computational overhead.
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Published in Expert Systems with Applications, 2026
Priyanka Choudhary and Somnath Dey
This paper addresses the challenge of recognizing traffic signs in poor visibility under varying light conditions. It employs a two-step approach: find the lighting quality of image and then based on that quality enhance image if quality lies below some threshold. Then employ YOLOv8 to detect the traffic signs.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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