Publications
This page includes my academic publications and research contributions. My research interests focus on Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Remote Sensing, image analysis, intelligent systems, and data-driven decision-making.
You can also find my publications on my ORCID profile.
2026
- Salman Alsalman and Amina Salhi. “HCFFormer: A Hybrid CNN–Transformer Framework for Heterogeneous Remote Sensing Image Change Detection.” International Journal of Remote Sensing, 2026.
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2025
- Srigouri Kosuri, Abdurasul Bobonazarov, Shazia Ali, Salman Alsalman, S. Suma Christal Mary, and R. Dhaaraani. “Modeling Employee Emotional Intelligence Progression Using Self-Supervised Deep Learning and Longitudinal Organizational Behavior Datasets.” 2025 IEEE Pune Section International Conference (PuneCon), pp. 1–6, 2025.
[paper link] - Biru Rajak, Salman Alsalman, Maksudjon Usmonov, Rohit Markan, G. Sajiv, and M. Ponni Valavan. “Energy-Efficient Ubiquitous Sensor Collaboration System Enhancing Real-Time Decision Making in IoT Ecosystems.” 2025 IEEE 2nd International Conference on Green Industrial Electronics and Sustainable Technologies (GIEST), 2025.
[paper link]
2015
- A. Ahmed Biyabani, Salman A. Al-Salman, and K. S. Alkhalaf. “Embedded Real-Time Bilingual ALPR.” 2015 International Conference on Communications, Signal Processing, and their Applications (ICCSPA), pp. 1–6, 2015.
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Selected Academic Projects (during graduate studies)
Malaria Cell Detection Using Curriculum Learning and Faster R-CNN (2023)
Explored Faster R-CNN and curriculum learning using Detectron2 and the M5-Malaria dataset. Converted annotations to COCO format and evaluated detection across different microscopes and magnifications.
Large-Scale Analysis of Citation Bias (2019)
Analysed San Diego traffic-stop records from the Stanford Open Policing Project. Applied data cleaning and feature selection, comparing neural networks, decision trees, and random forests to examine patterns in ticket issuance.
Efficient Liver Disease Prediction (2017)
Compared seven classifiers on the Indian Liver Patient Dataset using Python and scikit-learn. Preprocessed patient biomarker data and evaluated models using accuracy, confusion matrices, and execution time.
Predicting Safety Risks from Street View Photos (2017)
Explored crime-risk classification using street-view imagery and crime records from five U.S. cities. Combined image collection and cleaning, spatial clustering, and support vector machine classification.
