Jayakrishnan A

Jayakrishnan A

Assistant Professor

Publications

đź“ť Journal Articles

1. Jayakrishnan Anandakrishnan, Venkatesan Meenakshi Sundaram, and Prabhavathy Paneer. “STA-AgriNet: A Spatio-Temporal Attention Framework for Crop Type Mapping from Fused Multi-Sensor Multi-Temporal SITS”. In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 18 (2025), pp. 1817–1826. doi: 10.1109/JSTARS.2024.3510468. [SCIE, Q1][IF: 5.3].

2. Arun Kumar Sangaiah, Jayakrishnan Anandakrishnan, Sujith Kumar, Gui-Bin Bian, Salman A. AlQahtani, and Dirk Draheim. “Point-KAN: Leveraging Trustworthy AI for Reliable 3D Point Cloud Completion With Kolmogorov Arnold Networks for 6G-IoT Applications”. In: IEEE Internet of Things Journal (2025), pp. 1–1. doi: 10.1109/JIOT.2025.3576434. [SCIE, Q1][IF: 8.9].

3. Arun Kumar Sangaiah, Jayakrishnan Anandakrishnan, Nguyen Khanh Son, Hendri Darmawan, Gui-Bin Bian, and Mohammed J. F. Alenazi. “LCUT-Sv9: UAV-Assisted Powerline Inspection Framework with Secure Time-Sensitive Communication for Industry 5.0”. In: IEEE Open Journal of the Communications Society (2025), pp. 1–1. doi: 10.1109/OJCOMS.2025.3537105. [SCIE, Q1][IF: 6.1].

4. Jayakrishnan Anandakrishnan, Arun Kumar Sangaiah, Hendri Darmawan, Nguyen Khanh Son, Yi-Bing Lin, and Mohammed J. F. Alenazi. “Precise Spatial Prediction of Rice Seedlings From Large Scale Airborne Remote Sensing Data Using Optimized Li-YOLOv9”. In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024), pp. 1–13. doi: 10.1109/JSTARS.2024.3505964. [SCIE, Q1][IF: 5.3].

5. Jayakrishnan Anandakrishnan, Venkatesan M Sundaram, and Prabhavathy Paneer. “CERMF-Net: A SAR-Optical Feature Fusion for Cloud Elimination From Sentinel-2 Imagery Using Residual Multiscale Dilated Network”. In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 17 (2024), pp. 11741–11749. doi: 10.1109/JSTARS.2024.3411032. [SCIE, Q1][IF: 5.3].

6. Arun Kumar Sangaiah, Jayakrishnan Anandakrishnan, Aniruth Reddy Devarapelly, Muhammad Luqman Arif Bin Mohamad, Gui-Bin Bian, Mohammed J. F. Alenazi, and Salman A. AlQahtani. “R-UAV-Net: Enhanced YOLOv4 With Graph-Semantic Compression for Transformative UAV Sensing in Paddy Agronomy”. In: IEEE Transactions on Cognitive Communications and Networking (2024), pp. 1–1. doi: 10.1109/TCCN.2024.3452053. [SCIE, Q1][IF: 7.0].

7. Arun Kumar Sangaiah, Jayakrishnan Anandakrishnan, Venkatesan Meenakshisundaram, Mohd Amiruddin Abd Rahman, Padmapriya Arumugam, and Mrinali Das. “Edge-IoT-UAV Adaptation Toward Precision Agriculture Using 3D-LiDAR Point Clouds”. In: IEEE Internet of Things Magazine (2024), pp. 1–7. doi: 10.1109/IOTM.001.2400027. [SCOPUS].

8. Alkha Mohan, Venkatesan M., Prabhavathy P., and Jayakrishnan Anandakrishnan. “Temporal convolutional network based rice crop yield prediction using multispectral satellite data”. In: Infrared Physics & Technology 135 (2023), p. 104960. issn: 1350-4495. doi: https://doi.org/10.1016/j.infrared.2023.104960. [SCIE, Q2][IF: 3.4].

9. A. K. R, G. C, V. R. A, V. M, and Jayakrishnan Anandakrishnan. “Crop Classification using Semi supervised Learning on Data Fusion of SAR and Optical Sensor”. In: International Research Journal on Advanced Science Hub 5.Issue 05S (2023), pp. 443–453.

🎤 Conference Papers

1. Jayakrishnan Anandakrishnan, Arun Kumar Sangaiah, Nguyen Khanh Son, Shivani Kumari, Muhammad Luqman Arif, and Mohd Amiruddin Abd Rahman. “UAV-Based Deep Learning with Tiny-YOLOv9 for Revolutionizing Paddy Rice Disease Detection”. In: 2024 IEEE International Conference on Smart Internet of Things (SmartIoT). 2024, pp. 16–21. doi: 10.1109/SmartIoT62235.2024.00012. [SCOPUS].

2. Jayakrishnan Anandakrishnan, M Venkatesan, and P Prabhavathy. “MAE-CG: A Multi-Attention Enhanced Thin Cloud-Removal Generative Adversarial Network for Airborne Imagery”. In: IEEE 2024 India Geoscience and Remote Sensing Symposium (InGARSS 2024). 2024. [SCOPUS].

3. Jayakrishnan Anandakrishnan, M Venkatesan, P Prabhavathy, Santhana Krishnan J, Pavithra G, Dhanalakshmi R, and Amishaa S. “Hybrid 3D-2D Deep Multi-Source Fusion Framework for Cloud Removal from SAR-Optical Data”. In: IEEE 2024 India Geoscience and Remote Sensing Symposium (InGARSS 2024). 2024. [SCOPUS].

4. Jayakrishnan Anandakrishnan, M Venkatesan, P Prabhavathy, and Mohan Alkha. “MSDF-Net: A Multi-Scale Deep Fusion Network with Dilated Convolutions for Cloud Removal from Sentinel-2 Imagery”. In: IEEE 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). 2023, pp. 63–70. doi: 10.1109/APSIPAASC58517.2023.10317471. [SCOPUS].

đź“– Book Chapters

1. Jayakrishnan Anandakrishnan, M Venkatesan, P Prabhavathy, and Alkha Mohan. “A Parallel Attention Guided Generative Adversarial Network for Efficient Thin Cloud Removal from Satellite Imagery”. In: Generative Adversarial Networks for Remote Sensing. Ed. by Karbhari Vishwanth Kale, Amol Dattatraya Vibhute, Rajesh Kumar Dhanaraj. IGI Global, 2025. [SCOPUS].

2. Alkha Mohan, Jayakrishnan Anandakrishnan, M Venkatesan, and P Prabhavathy. “T-HyC : A Transfer Learning-based Multi-Scale 3D-2D Feature Aggregation for Hyperspectral Image Classification”. In: Computational Intelligence Based Hyperspectral Image Analysis and Applications. Ed. by Ajith Abraham and Anu Bajaj. Springer Nature, 2025. [SCOPUS].

3. Alkha Mohan and Jayakrishnan Anandakrishnan. “Leaf-CAP: A Capsule Network-Based Tea Leaf Disease Recognition and Detection”. In: Predictive Analytics in Smart Agriculture. Ed. by S. Krishnan, A. J. Anand, N. Prasanth, S. Goundar, and C. Ananth. CRC Press, 2023. [SCOPUS].