RealVisor: AI-Powered Real Estate Analytics
An end-to-end AI analytics platform for property valuation and market trend analysis using XGBoost and Streamlit.
Posts by Collection
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
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publications
AHF-RBFNet: Attention-Guided Hierarchical Fusion U-Net with Learnable Fuzzy Membership Kernels for Medical Image Segmentation
Integrating a learnable Radial Basis Function (RBF) fuzzy membership kernel into a hierarchical U-Net to dynamically filter semantic uncertainty, achieving SOTA IoU on skin lesion datasets.
Recommended citation: L. Chhetri, et al. (2026). "AHF-RBFNet: Attention-Guided Hierarchical Fusion U-Net with Learnable Fuzzy Membership Kernels for Medical Image Segmentation." In Progress.
Degraded Ancient Ashokan Brahmi Script Recognition via Self-Supervised Pretraining and WGAN-GP Degradation Pipelines
An end-to-end OCR and visual inpainting framework for ancient Indic scripts, introducing a 150K sequence dataset generated via physically-motivated WGAN-GP degradation.
Recommended citation: L. Chhetri, et al. (2026). "Degraded Ancient Ashokan Brahmi Script Recognition via Self-Supervised Pretraining and WGAN-GP Degradation Pipelines." In Progress.
Geometric Residual Learning for 3D Medical Image Segmentation via DDL-Mamba
A novel Delta-Mamba framework integrating Deep Delta Learning blocks into a 3D U-Mamba backbone, featuring Softplus-constrained weights to stabilize representation drift in dense 3D State Space Models.
Recommended citation: L. Chhetri, et al. (2026). "Geometric Residual Learning for 3D Medical Image Segmentation via DDL-Mamba." In Progress.
Ionospheric TEC Forecasting via Deep Delta Learning and Conformal Prediction
A CNN-DDL architecture featuring a dynamic beta-gate and Marginal Split Conformal Prediction for real-time solar wind modeling, achieving zero-shot cross-solar-cycle generalization.
Recommended citation: A. Kumar, L. Chhetri, P. Ghosal. (2026). "Zero-Shot Cross-Solar Cycle Generalization of Ionospheric Total Electron Content Dynamics using a Deep Delta Learning Convolutional Neural Network." Advances in Space Research (Under Review).
Deep Delta Vision Mamba: A Lightweight State Space Architecture with Deep Delta Learning for Efficient Remote Sensing
A hierarchical State Space Model (SSM) architecture integrating 2D Deep Delta Learning, achieving 510 FPS and outperforming ResNet50 by 13.1x in deployment efficiency for satellite edge computing.
Recommended citation: L. Chhetri, A. Kumar, G. Sarma. (2026). "Deep Delta Vision Mamba: A Lightweight State Space Architecture with Deep Delta Learning for Efficient Remote Sensing." IEEE CONECCT.
Optimizing Deep Learning for Brain Tumor Classification: A Comparative Ablation Study of Preprocessing and Augmentation Strategies
A comprehensive ablation study isolating the impact of specific data preprocessing and augmentation pipelines, proposing a novel “destructive vs. constructive” taxonomy for medical image processing.
Recommended citation: L. Chhetri, A. Kumar. (2026). "Optimizing Deep Learning for Brain Tumor Classification: A Comparative Ablation Study of Preprocessing and Augmentation Strategies." IEEE GCON.
DDV-GNet: High-Throughput Defect Detection for Space Manufacturing via Deep Delta Gated Networks
A novel hierarchical gated convolutional architecture achieving real-time processing (853 FPS) and 95.9% accuracy for space manufacturing defect detection.
Recommended citation: L. Chhetri, A. Kumar. (2026). "DDV-GNet: High-Throughput Defect Detection for Space Manufacturing via Deep Delta Gated Networks." IEEE SPACE.
Beyond Limited Labels: Safe Semi-Supervised Learning for Malaria Diagnosis
An uncertainty-guided semi-supervised learning framework that integrates Monte Carlo dropout-based epistemic uncertainty estimation to reduce silent failure rates by 29.2% in resource-constrained environments.
Recommended citation: L. Chhetri, Aman Kumar. (2026). "Beyond Limited Labels: Safe Semi-Supervised Learning for Malaria Diagnosis." IEEE DSAA (Under Review).
Attention-Enhanced Swin Transformers for Robust Brain Tumor Classification Under Patient-Level Data Splitting
We propose an Attention-Enhanced Swin Transformer integrating hierarchical windowed attention with CBAM to mitigate data leakage, achieving 96.82% accuracy on strict patient-level splits.
Recommended citation: L. Chhetri, P. Ghosal, A. Datta. (2026). "Attention-Enhanced Swin Transformers for Robust Brain Tumor Classification Under Patient-Level Data Splitting." IEEE GCON.
Intrinsic Neural Firewalls for Cyber-Physical Systems: Robust Anomaly Rejection via Deep Delta Residual Overwrites
An intrinsic defense architecture (DDL-FW) for Cyber-Physical Systems that embeds anomaly detection directly into residual connections, achieving an F1 score of 0.7206 on the HAI 21.03 benchmark.
Recommended citation: 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 (Under Review).
Risk-Controlled Urban Change Detection: Conformal Prediction Wrappers for Provable Reliability in High-Resolution Satellite Imagery
A rigorous statistical approach applying Marginal Split Conformal Prediction to transformer-based satellite change detection, achieving distribution-free coverage bounds and SOTA F1 scores.
Recommended citation: A. Kumar, A. Mukherjee, H. Das, L. Chhetri, P. Ghosal. (2026). "Risk-Controlled Urban Change Detection: Conformal Prediction Wrappers for Provable Reliability in High-Resolution Satellite Imagery." ICCI (Under Review).
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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