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Lijin P.

Assistant Professor, School of Artificial Intelligence, Bengaluru

Qualification: M. Sc., M. Tech.
p_lijin@blr.amrita.edu
Google Scholar Profile
Research Interest: Bio-Medical Image Processing, Computer Vision

Bio Publications
Bio

Lijin P. holds an M. Tech. and an M. Sc. in Computer Science from Pondicherry University, and a B. Sc. in Computer Science from the University of Calicut. He has submitted his Ph. D. thesis at Cochin University of Science and Technology, Kerala, and is currently awaiting his defense. He was awarded a Visiting Scholar Fellowship by the Research Council of Norway, where he collaborated closely with the Norwegian University of Science and Technology (NTNU). His research interests lie in biomedical image processing and computer vision.

Publications

Conference Paper

Year : 2024

TransNet: Advancing Colonoscopy Polyp Segmentation Through Transformer Integration

Cite this Research Publication : P. Lijin, G. Santhosh Kumar, Madhu S. Nair, TransNet: Advancing Colonoscopy Polyp Segmentation Through Transformer Integration, International Conference on e-Health and Bioengineering, IFMBE Proceedings, Springer Nature Switzerland, 2024, https://doi.org/10.1007/978-3-031-62523-7_39

Publisher : Springer Nature Switzerland

Year : 2024

Dual Encoder-Decoder U-Net Architecture for Polyp Segmentation in Colonoscopy Images with Shuffle Attention and Conditional Random Fields

Cite this Research Publication : Lijin P., Santhosh Kumar G., Madhu S. Nair, Dual Encoder-Decoder U-Net Architecture for Polyp Segmentation in Colonoscopy Images with Shuffle Attention and Conditional Random Fields, 2024 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), IEEE, 2024, https://doi.org/10.1109/conecct62155.2024.10677050

Publisher : IEEE

Journal Article

Year : 2024

PolySegNet: improving polyp segmentation through swin transformer and vision transformer fusion

Cite this Research Publication : P. Lijin, Mohib Ullah, Anuja Vats, Faouzi Alaya Cheikh, G. Santhosh Kumar, Madhu S. Nair, PolySegNet: improving polyp segmentation through swin transformer and vision transformer fusion, Biomedical Engineering Letters, Springer Science and Business Media LLC, 2024, https://doi.org/10.1007/s13534-024-00415-x

Publisher : Springer Science and Business Media LLC

Year : 2024

EfficientPolypSeg: Efficient Polyp Segmentation in colonoscopy images using EfficientNet-B5 with dilated blocks and attention mechanisms

Cite this Research Publication : Lijin P., Mohib Ullah, Anuja Vats, F.A. Cheikh, Santhosh Kumar G., Madhu S. Nair, EfficientPolypSeg: Efficient Polyp Segmentation in colonoscopy images using EfficientNet-B5 with dilated blocks and attention mechanisms, Biomedical Signal Processing and Control, Elsevier BV, 2024, https://doi.org/10.1016/j.bspc.2024.106210

Publisher : Elsevier BV

Year : 2024

Dual Encoder–Decoder Shifted Window-Based Transformer Network for Polyp Segmentation With Self-Learning Approach

Cite this Research Publication : Lijin P., Mohib Ullah, Anuja Vats, Faouzi Alaya Cheikh, Santhosh Kumar G., Madhu S. Nair, Dual Encoder–Decoder Shifted Window-Based Transformer Network for Polyp Segmentation With Self-Learning Approach, IEEE Transactions on Artificial Intelligence, Institute of Electrical and Electronics Engineers (IEEE), 2024, https://doi.org/10.1109/tai.2024.3366146

Publisher : Institute of Electrical and Electronics Engineers (IEEE)

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