DEEP LEARNING-BASED OIL SPILL DETECTION USING SATELLITE IMAGERY: A DOMAIN ADAPTATION APPROACH FOR OFFSHORE MONITORING M. Sh. Aghalarov, L. G. Muradkhanli Socar Proceedings, 2026 Effective monitoring of oil spills is critical for environmental protection and operational safety in offshore oil and gas production areas. This study presents an automated oil spill detection system for the offshore environment using satellite imagery and advanced deep learning techniques. A key challenge in deploying AI-based detection systems is the scarcity of annotated training data, as manual pixel-level labeling of oil spill imagery is both time-consuming and costly, particularly in large-scale maritime settings. To address this limitation, we propose a domain adaptation methodology that combines synthetically generated training data with unsupervised domain adaptation techniques, significantly reducing annotation requirements while improving generalization across diverse environmental conditions. Our approach integrates temporal fusion of multi-temporal satellite imagery, Discrete Cosine Transform (DCT) frequency domain processing, and adversarial domain adaptation to effectively bridge the distributional gap between synthetic and real satellite imagery. Experimental results demonstrate that the proposed SegFormer-B3 architecture achieves 71.3% Intersection over Union (IoU) for oil spill detection, representing a 73% relative improvement over baseline methods trained only on automatically annotated data. The system efficiently processes periodic satellite coverage within operational timeframes, enabling automated first-line screening with human oversight for timely and informed response. This methodology addresses a critical need in offshore operations, providing a cost-effective and scalable solution for environmental monitoring that substantially reduces manual annotation effort while maintaining high detection accuracy across varying sea surface conditions. Keywords: semantic segmentation; computer vision; satellite imagery; domain adaptation; discrete cosine transform.
Smart City Through Big Data Integration Kamala Oghuz, Leyla Muradkhanli, Minaya Musayeva, Elnur Badalov 2025 10th International Conference on Energy Efficiency and Agricultural Engineering EE and Ae 2025 Conference Proceedings, 2025
Artificial Intelligence Techniques in Improving the Quality of Services Provided by E-Government to Citizens Mohammad Ali Al Qudah, Leyla Muradkhanli, Anas A. Salameh, Mudasir Ali Rind, Zeynab Muradkhanli 2024 IEEE 1st Karachi Section Humanitarian Technology Conference Khi Htc 2024, 2024 The purpose of the study was to determine how much of an impact artificial intelligence has had on the process of boosting user confidence and the quality of services provided by the government online. Specifically, the study wanted to know how much of an impact artificial intelligence has had on the process of upgrading government services. Capabilities The development of AI-based tools and solutions has made it possible for more businesses to reap the benefits of AI at a cheaper cost and in a more expedient manner. In the context of artificial intelligence, the term “off-the-shelf AI” refers to solutions, tools, and software that either have AI capabilities built in or automate algorithmic decision-making. Ready-to-use Government applications of AI can include autonomous databases that use machine learning to self-heal, as well as prebuilt models that address problems like iris recognition and text analysis across various datasets. Both examples are examples of what are known as autonomous databases. It may help businesses achieve value more quickly while also increasing productivity, lowering costs, and improving their connections with customers. Artificial intelligence has significantly contributed to the evolution of government services, and today, it is widely regarded as one of the most essential building blocks of e-government. Because of these gadgets, it is now much simpler for huge organizations and governments to build a specific system and strategy that assists in gaining access to electronic services.
Using Artificial Intelligence Applications For E-Government Services As Iris Recognition Mohammad Ali Al Qudah, Leyla Muradkhanli, Zeynab Muradkhanli, Anas A. Salameh 17th IEEE International Conference on Application of Information and Communication Technologies Aict 2023 Proceedings, 2023 E-government is defined as the effective integrated use of all information and communication technologies to facilitate the daily administrative operations of government sectors. The revolution in digital communication technologies has put more pressure on many public sector institutions to transform their operations into the world of electronic business. This is what is known as e-government. E-government is defined as the effective integrated use of all information and communication technologies. People are recognised by the use of their fingerprints, faces, hand geometries, and iris prints, among other biometric characteristics. This research intends to use iris recognition to identify people through the image of the iris and apply a programme using Python and the deep learning method of a convolutional neural network (CNN) to match the printed iris images of people, where the images match the images of people and show the name of the person who owns this photo. This research also intends to use the deep learning method to match the printed iris images of people. This is a contemporary system that aids in the identification of individuals and replaces e-government systems with smart systems that incorporate artificial intelligence into their operations to deliver the best services possible to residents. How much does the Jordanian government want to employ biometric characteristics, such as the iris of the eye, which is regarded as part of the biometric features, in all of the electronic government services.
Implementation of eLearning in Azerbaijan Leyla Muradkhanli, Bahram Atabeyli 2012 6th International Conference on Application of Information and Communication Technologies Aict 2012 Proceedings, 2012 This article discusses the experience of implementation of eLearning in Azerbaijan. Various factors contributing to the success and challenges of eLearning implementation are also discussed.
Blended learning: The integration of traditional learning and eLearning L.G. Muradkhanli 2011 5th International Conference on Application of Information and Communication Technologies Aict 2011, 2011 The article considers an analysis of the delivery methods using traditional learning, eLearning, and blended learning. Analysis of the comparison between traditional learning and eLearning has been done. The characteristics and benefits of blended learning are analyzed. Blended learning course development steps are described.
RECENT SCHOLAR PUBLICATIONS
Augmented Reality in Logo Design: Towards an Interactive Brand Experience in the Digital Space MM Abuhashish, L Muradkhanli, M Hamdan 2025 IEEE 19th International Conference on Application of Information and … , 2025 2025
Optimizing Human Detection in Natural Disaster Environments Through YOLO and Image Processing L Muradkhanli 2025 IEEE 19th International Conference on Application of Information and … , 2025 2025
Measuring the importance of augmented reality applications in educational curricula MM Abuhashish, L Muradkhanli, MAAL Qudah Problems of Information Society, 34-42 , 2025 2025
Fire detection using image processing L Muradkhanli Journal of Engineering Sciences and Modern Technologies 1 (1) , 2025 2025
Development index and the challenges of adopting artificial intelligence in improving the quality of e-government services to citizens in Jordan MA ALQudah, L Muradkhanli Problems of Information Society, 30-42 , 2024 2024 Citations: 7
The use of generative artificial intelligence for customer services MA Alqudah Available at SSRN 4771265 , 2024 2024 Citations: 6
Implementation of artificial intelligence by using amazon web services to improve services in e-government MA Al Qudah, L Muradkhanli, M Abuhashish Problems of Information Society 15 (2), 71-81 , 2024 2024 Citations: 3
Artificial Intelligence Techniques In Improving the Quality of Services Provided By E-Government To Citizens MA Al Qudah, L Muradkhanli, AA Salameh, MA Rind, Z Muradkhanli 2024 IEEE 1st Karachi Section Humanitarian Technology Conference (KHI-HTC), 1-4 , 2024 2024 Citations: 2
Building IOS App for Language Learning L Muradkhanli, I Samadova Khazar University Press , 2024 2024
Hala hamdan, Mutaz Mohammed Abuhashish. Big Data Enables E-Government to Implement Sustainable Development MAAL Qudah, L Muradkhanli, HA Weshah International International Journal on Orange Technologies (IJOT) 6 (4), 40-52 , 2024 2024 Citations: 3
Using Artificial Intelligence applications for E-Government services as iris recognition MA Al Qudah, L Muradkhanli, Z Muradkhanli, AA Salameh 2023 IEEE 17th International Conference on Application of Information and … , 2023 2023 Citations: 12
Customer behavior analysis using big data analytics and machine learning LG Muradkhanli, ZM Karimov Problems of Information Society, 61-67 , 2023 2023 Citations: 3
Face spoof detection using convolutional neural network LG Muradkhanli, PA Namazli Problems of Information Society, 40-46 , 2023 2023 Citations: 1
Discovering the Contrasts between Augmented Reality and Virtual Reality in Teaching University Courses MM Abuhashish, L Muradkhanli 2023
The Impact of Augmented Reality Application Development on University Teaching Curricula MM Abuhashish, L Muradkhanli Khazar University Press , 2023 2023
Real-time face detection on a Raspberry PI LG Muradkhanli, EA Mammadov Problems of Information Society, 38-45 , 2022 2022 Citations: 3
Mitigating Resource Management and Continuous Integration Obstacles in Heavy Traffic Systems Using Containerization and Orchestration Tools T Ahmadov, L Muradkhanli Khazar University Press , 2022 2022
Artificial intelligence applications that support: Business organizations and e-government in administrative decision MA Alqudah, L Muradkhanli Available at SSRN 3866216 , 2021 2021 Citations: 10
E-government in Jordan and studying the extent of the e-government development index according to the United Nations report MA Alqudah, L Muradkhanli International Journal of Multidisciplinary: Applied Business and Education … , 2021 2021 Citations: 21
Electronic management and its role in developing the performance of e-government in Jordan MA Alqudah, L Muradkhanli Electronic Research Journal of Engineering, Computer and Applied Sciences 3 … , 2021 2021 Citations: 34
MOST CITED SCHOLAR PUBLICATIONS
Neural networks for prediction of oil production L Muradkhanli IFAC-PapersOnLine 51 (30), 415-417 , 2018 2018 Citations: 39
Electronic management and its role in developing the performance of e-government in Jordan MA Alqudah, L Muradkhanli Electronic Research Journal of Engineering, Computer and Applied Sciences 3 … , 2021 2021 Citations: 34
E-government in Jordan and studying the extent of the e-government development index according to the United Nations report MA Alqudah, L Muradkhanli International Journal of Multidisciplinary: Applied Business and Education … , 2021 2021 Citations: 21
Artificial intelligence in electric government; ethical challenges and governance in Jordan MA Alqudah, L Muradkhanli Electronic Research Journal of Social Sciences and Humanities 3, 65-74 , 2021 2021 Citations: 21
Safer design and less cost operation for low-traffic long-road illumination using control system based on pattern recognition technique M Mahmoud, L Muradkhanli Intelligent Control and Automation 11 (03), 47 , 2020 2020 Citations: 17
Using Artificial Intelligence applications for E-Government services as iris recognition MA Al Qudah, L Muradkhanli, Z Muradkhanli, AA Salameh 2023 IEEE 17th International Conference on Application of Information and … , 2023 2023 Citations: 12
Expert system for decision-making problem in economics A Alasgarova, L Muradkhanli International Journal “Information Technologies and Knowledge 2, 297-299 , 2008 2008 Citations: 12
Artificial intelligence applications that support: Business organizations and e-government in administrative decision MA Alqudah, L Muradkhanli Available at SSRN 3866216 , 2021 2021 Citations: 10
Economical and Safe Design for Low-Traffic Long-Roads Illumination Control System by Using Image Recognition MMAS Mahmoud, L Muradkhanli Journal of Electrical and Electronic Engineering 8 (5), 117-126 , 2020 2020 Citations: 9
Development index and the challenges of adopting artificial intelligence in improving the quality of e-government services to citizens in Jordan MA ALQudah, L Muradkhanli Problems of Information Society, 30-42 , 2024 2024 Citations: 7
The use of generative artificial intelligence for customer services MA Alqudah Available at SSRN 4771265 , 2024 2024 Citations: 6
Implementation of eLearning in Azerbaijan L Muradkhanli, B Atabeyli 2012 6th International Conference on Application of Information and … , 2012 2012 Citations: 5
Implementation of artificial intelligence by using amazon web services to improve services in e-government MA Al Qudah, L Muradkhanli, M Abuhashish Problems of Information Society 15 (2), 71-81 , 2024 2024 Citations: 3
Hala hamdan, Mutaz Mohammed Abuhashish. Big Data Enables E-Government to Implement Sustainable Development MAAL Qudah, L Muradkhanli, HA Weshah International International Journal on Orange Technologies (IJOT) 6 (4), 40-52 , 2024 2024 Citations: 3
Customer behavior analysis using big data analytics and machine learning LG Muradkhanli, ZM Karimov Problems of Information Society, 61-67 , 2023 2023 Citations: 3
Real-time face detection on a Raspberry PI LG Muradkhanli, EA Mammadov Problems of Information Society, 38-45 , 2022 2022 Citations: 3
Artificial Intelligence Techniques In Improving the Quality of Services Provided By E-Government To Citizens MA Al Qudah, L Muradkhanli, AA Salameh, MA Rind, Z Muradkhanli 2024 IEEE 1st Karachi Section Humanitarian Technology Conference (KHI-HTC), 1-4 , 2024 2024 Citations: 2
Face spoof detection using convolutional neural network LG Muradkhanli, PA Namazli Problems of Information Society, 40-46 , 2023 2023 Citations: 1
Augmented Reality in Logo Design: Towards an Interactive Brand Experience in the Digital Space MM Abuhashish, L Muradkhanli, M Hamdan 2025 IEEE 19th International Conference on Application of Information and … , 2025 2025
Optimizing Human Detection in Natural Disaster Environments Through YOLO and Image Processing L Muradkhanli 2025 IEEE 19th International Conference on Application of Information and … , 2025 2025
