Md. Al-Masrur Khan

Engineering · Indiana University

Infrastructure Maintenance and Monitoring Asphalt Pavement Performance Evaluation Advanced Neural Network Applications Domain Adaptation and Few-Shot Learning Concrete Corrosion and Durability

Publications

Citations

799

Est. group size

—

Recurring co-author estimate

Active years

Publishing since 2019

Research summary

AI-generated

Md. Al-Masrur Khan works at the intersection of engineering and machine learning, developing deep learning and computer vision methods for practical problems. Much of the work focuses on automated visual inspection of infrastructure (such as detecting cracks in concrete and pavements) and on applying machine learning to medical and biological data, including disease diagnosis and image classification. The research also covers techniques like domain adaptation and semantic segmentation, which help AI models work reliably across different types of images.

Deep learning for infrastructure crack detectionComputer vision and semantic segmentationMachine learning for medical diagnosisDomain adaptation and few-shot learningRobotics and autonomous vehicle perception

Publication activity grew notably over the decade, rising from about one paper per year up to 2021 to a peak of nine in 2023, then settling at a few per year.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026

Publication cadence

Publications per year over the last 10 years — averaging 3.4/year recently

Recent publications

Heterogeneous virus classification using a functional deep learning model based on transmission electron microscopy images
Scientific Reports · 2024
Heterogeneous virus classification using a functional deep learning model based on transmission electron microscopy images (Preprint)
arXiv (Cornell University) · 2024
C^2DA: Contrastive and Context-aware Domain Adaptive Semantic Segmentation
arXiv (Cornell University) · 2024
Detection of the chronic kidney disease using XGBoost classifier and explaining the influence of the attributes on the model using SHAP
Scientific Reports · 2023
Human Activity Recognition Using Attention-Mechanism-Based Deep Learning Feature Combination
Sensors · 2023
Image Processing Techniques for Concrete Crack Detection: A Scientometrics Literature Review
Remote Sensing · 2023
Deep-Learning-Based Semantic Segmentation for Remote Sensing: A Bibliometric Literature Review
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2023
Vision-Based Concrete-Crack Detection on Railway Sleepers Using Dense U-Net Model
Algorithms · 2023
A Modified Aquila-Based Optimized XGBoost Framework for Detecting Probable Seizure Status in Neonates
Sensors · 2023
Development of AI- and Robotics-Assisted Automated Pavement-Crack-Evaluation System
Remote Sensing · 2023
Vision-Based Concrete-Crack Detection on Railway Sleepers Using Dense U-net Model
Preprints.org · 2023
Development of AI and Robotics Assisted Automated PavementCrack Evaluation System
Preprints.org · 2023
IoT-Based Healthcare-Monitoring System towards Improving Quality of Life: A Review
Healthcare · 2022
LLDNet: A Lightweight Lane Detection Approach for Autonomous Cars Using Deep Learning
Sensors · 2022
Finding the influential clinical traits that impact on the diagnosis of heart disease using statistical and machine-learning techniques
Scientific Reports · 2022

Publishes in

Scientific Reports×3
Sensors×3
arXiv (Cornell University)×3
Remote Sensing×2
Preprints.org×2

This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 11, 2026.

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