Sami Rashid
- Intern, CCDS
Research Interests
Machine Learning
Conference Paper2025
Resolution, Compression, and GAN-Enhanced Evaluation of YOLO Models on the Poribohon-BD Vehicle Dataset
Sabrina Masum Meem, Mohammed Tahmid Hossain, Sami Rashid, Ashraful Islam, Rashedur Rahman, Istiaq Ahmed, Asif Mahmud, Saadia Binte Alam, M Ashraful Amin
2025 IEEE 23rd Student Conference on Research and Development (SCOReD)
IEEE, pp. 1-6
Abstract
Object detection in resource-constrained environments poses challenges for real-time intelligent transportation systems (ITS), where low resolution, compression artifacts, and bandwidth limitations hinder performance. This study evaluates YOLOv8, YOLOv10, and YOLOv12 on the Poribohon-BD dataset of 15 native Bangladeshi vehicle classes using three dataset variants: resized images, JPEG-compressed images (Q50, Q75), and GAN-enhanced images restored with Real-ESRGAN. The results show that resolution is the dominant factor, and YOLOv8 delivers the most stable performance under all conditions. YOLOv10 generalized slightly better at very low resolutions, while YOLOv12 was competitive at higher resolutions under compression and GAN restoration but degraded at lower scales. GAN enhancement improved accuracy only when there was sufficient base resolution, revealing a gap between perceptual fidelity and detection accuracy. Overall, these findings provide a systematic framework for selecting YOLO architectures and preprocessing pipelines under degraded inputs, supporting deployment in real-world ITS.
Keywords
- YOLOv12
- YOLOv10
- Real-ESRGAN
- intelligent transportation systems
- YOLOv8
- resource-constrained environments
- vehicle detection
- Image resolution
- JPEG compression
CCDS Authors
Ashraful Islam, PhD
- Center Director, CCDS
- Director, HCI Wing
Assistant Professor
Department of Computer Science and Engineering
Independent University, Bangladesh (IUB)Published at
CHI, UIST, UbiComp, IJCNN, ICIP, HCII, ICDMW, BLP, IEEE Internet of Things Journal, JMIR, JMIR Human Factors, JMIR Formative Research, IEEE Access, Smart Agricultural Technology, Diabetes Research and Clinical Practice, PLOS ONE
Research Interests
Human-Computer Interaction, AI for Social Good, AI for Public Health, AI for Impact
Md. Rashedur Rahman, D. Eng.
- Co-Director, MIRA & NEST Wings
Assistant Professor
Department of Computer Science and Engineering
Independent University, Bangladesh
Published at
CHI, HCII, Scientific Reports, Cognitive Computation, Neural Computing and Applications
Istiaq Ahmed
- Research Assistant, HCI Wing
Published at
CHI, HCII
Research Interests
mHealth, Human-Computer Interaction, Cross-Platform App/Website Development
Asif Mahmud
- Co-Director, IPT Wing
Lecturer
Department of Computer Science and Engineering
Independent University, Bangladesh
Saadia Binte Alam, PhD
- Director, MIRA & WiSE Wings
Associate Professor
Department of Computer Science and Engineering
Independent University, Bangladesh
Published at
HCII, Scientific Reports, Cognitive Computation, Neural Computing and Applications
Prof. M Ashraful Amin, PhD
- Founder Director, CCDS
- Director, AI/ML, HCI & DS Wings
Professor
+1 more affiliationDepartment of Information Sciences and Technology
George Mason University, USA
Published at
ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE
Research Interests
Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics
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