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Nazmus Saqib
Researcher (PhD.)
Jeju National University, South Korea · Computer Science and Engineering (CSE)
View Google Scholar
Current Affiliation
University
Jeju National University, South Korea
Department
Computer Science and Engineering (CSE)
Research Areas
Deep Learning
Computer Vision
Academic Background
Researcher (PhD.)
Jeju National University, South Korea
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Publications (14)
2025
STAM: Zero-shot Style Transfer using Diffusion Model via Attention Modulation
Proceedings of the Computer Vision and Pattern Recognition Conference
2023
Semi-supervised atmospheric component learning in low-light image problem
Plos one
2022
Denoising single images by feature ensemble revisited
Sensors
2020
Image classification using dnn with an improved optimizer
2020 IEEE Region 10 Symposium (TENSYMP)
2022
Rethinking Gradient Weight’s Influence over Saliency Map Estimation
Sensors
2021
LIGHT-LESS TO BRIGHTNESS VIA APPROXIMATING ATMOSPHERIC FACTORS: ASEMI-SUPERVISED PATH
2020
An improved adaptive optimization technique for image classification
2020 Joint 9th International Conference on Informatics, Electronics & Vision (ICIEV) and 2020 4th International Conference on Imaging, Vision & Pattern Recognition (icIVPR)
2025
CasF: A cascaded feature fusion CNN for fingerprint liveness detection
Available at SSRN 5218010
2026
Noise-Aware Multi-inference Self-regulation for Self-supervised Denoising
Pacific-Asia Conference on Knowledge Discovery and Data Mining
2026
OSEG: Improving Diffusion sampling through Orthogonal Smoothed Energy Guidance
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision
2025
Understanding the Role of CutMix in ETF During Neural Collapse
한국통신학회 인공지능 학술대회 논문집
2024
Regional Power Demand Forecasting Using BiLSTM and ConvBiLSTM Models for Sustainable Energy Management
2024 International Conference on Engineering and Emerging Technologies (ICEET)
2022
Denoising single images by feature ensemble revisited
arXiv e-prints
Supplementary material: OSEG: Improving Diffusion sampling through Orthogonal Smoothed Energy Guidance
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