Publications
My accepted manuscripts and under-review research.
Core Group Research
DDV-GNet: High-Throughput Defect Detection for Space Manufacturing via Deep Delta Gated Networks
L. Chhetri, A. Kumar. (2026). “DDV-GNet: High-Throughput Defect Detection for Space Manufacturing via Deep Delta Gated Networks.” IEEE SPACE (Accepted for Oral Presentation).
Deep Delta Vision Mamba: A Lightweight State Space Architecture with Deep Delta Learning for Efficient Remote Sensing
L. Chhetri, A. Kumar. (2026). “Deep Delta Vision Mamba: A Lightweight State Space Architecture with Deep Delta Learning for Efficient Remote Sensing.” IEEE CONECCT (Accepted).
Optimizing Deep Learning for Brain Tumor Classification: A Comparative Ablation Study of Preprocessing and Augmentation Strategies
L. Chhetri, A. Kumar. (2026). “Optimizing Deep Learning for Brain Tumor Classification: A Comparative Ablation Study of Preprocessing and Augmentation Strategies.” IEEE GCON (Accepted).
SPECTRAFORGE: Domain-Equalized Frequency-Spatial Fusion for Synthetic Dermatology Detection
A. Kumar, L. Chhetri, D. Das. (2026). “SPECTRAFORGE: Domain-Equalized Frequency-Spatial Fusion for Synthetic Dermatology Detection.” IEEE DSAA (Under Review).
Beyond Limited Labels: Safe Semi-Supervised Learning for Malaria Diagnosis
L. Chhetri, A. Kumar. (2026). “Beyond Limited Labels: Safe Semi-Supervised Learning for Malaria Diagnosis.” IEEE DSAA (Under Review).
Risk-Controlled Urban Change Detection: Conformal Prediction Wrappers for Provable Reliability in High-Resolution Satellite Imagery
A. Mukherjee, A. Kumar, S. R. Verma, H. Das, L. Chhetri. (2026). “Risk-Controlled Urban Change Detection: Conformal Prediction Wrappers for Provable Reliability in High-Resolution Satellite Imagery.” ICCI (Accepted for Oral Presentation).
Interpretable Solar Panel Defect Detection via Fuzzy Rule Extraction from Deep Learning Architectures
S. R. Verma, A. Kumar, A. Anand, H. Das, L. Chhetri. (2026). “Interpretable Solar Panel Defect Detection via Fuzzy Rule Extraction from Deep Learning Architectures.” ICCI (Under Review).
External Collaborations & Prior Work
Research conducted by Halo Mind members in collaboration with university Principal Investigators (PIs).
ClearVision: A Physics-Informed Lightweight GAN for Real-Time Enhancement of Turbid Underwater Imagery
R. Singh, D. Das, A. Pradhan. (2026). “ClearVision: A Physics-Informed Lightweight GAN for Real-Time Enhancement of Turbid Underwater Imagery.” IEEE OCEANS Sanya (Accepted for Oral Presentation).
Attention-Enhanced Swin Transformers for Robust Brain Tumor Classification Under Patient-Level Data Splitting
L. Chhetri, A. Datta, P. Ghosal. (2026). “Attention-Enhanced Swin Transformers for Robust Brain Tumor Classification Under Patient-Level Data Splitting.” IEEE GCON (Accepted).
Intrinsic Neural Firewalls for Cyber-Physical Systems: Robust Anomaly Rejection via Deep Delta Residual Overwrites
R. Das, L. Chhetri, A. Kumar, P. Ghosal. (2026). “Intrinsic Neural Firewalls for Cyber-Physical Systems: Robust Anomaly Rejection via Deep Delta Residual Overwrites.” WIN 6.0 (Accepted for Oral Presentation).
Benchmarking GAN Architectures for Underwater Imaging: The Trade-off Between Model Compactness and Real-Time Latency
D. Das, R. Singh, A. Pradhan, P. Ghosal. (2026). “Benchmarking GAN Architectures for Underwater Imaging: The Trade-off Between Model Compactness and Real-Time Latency.” IEEE GCON (Accepted).