Ankit Das

About

Ankit Das is an EPSRC/Hinduja PhD Research Scholar at the EPSRC CDT in Advanced Engineering for Personalised Surgery and Intervention (AE-PSI), affiliated with the School of Biomedical Engineering and Imaging Sciences, King’s College London.

Employment

Employment history is unavailable.

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (8)

• Interpretable lightweight attention-guided deep learning framework for retinal optic disc and optic cup segmentation
  Ankit Das, Saubhik Bandyopadhyay, Debapriya Banik +1 more
  Neural Computing and Applications 2026 DOI: 10.1007/s00521-026-12036-9
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• CResPIE-ViT: A Compact Vision Transformer-Based Framework for COVID-19 Lesion Segmentation and Severity Prediction
  Ankit Das, Debapriya Banik, Kaushiki Roy +2 more
  IEEE Transactions on Instrumentation and Measurement 2026 DOI: 10.1109/TIM.2026.3712909
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• Lw-CSAtt-Net: A Lightweight Multi-Attention Based Network for Glaucoma Prediction Using Retinal Fundus Images
  Lecture Notes in Networks and Systems 2026 DOI: 10.1007/978-981-96-7742-9_23
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• Analysis of Oversampling and Its Impact on an Imbalanced Dataset for Emoji Prediction from Tweets Using Machine Learning Techniques
  2025 DOI: 10.1007/978-981-97-8476-9_21
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• Lw-ResSASE-Net: A Lightweight Attention-Based Residual Network for Covid-19 and Pneumonia Prediction Using Chest X-Ray
  2024 DOI: 10.1109/C3IT60531.2024.10829470
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• CoViT-Net: A Pre-trained Hybrid Vision Transformer for COVID-19 Detection in CT-Scans
  Ankit Das, Debapriya Banik, Kaushiki Roy

  +2 more

  • Gordon K. T. Chan
  • Debotosh Bhattacharjee
  Lecture Notes in Networks and Systems 2024 DOI: 10.1007/978-981-97-2611-0_23
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• Lw-IRBCaSa-Net: A Lightweight Inverted Residual Network with CaSa Attention Module for Disease Prediction from CXR Images
  Lecture Notes in Networks and Systems 2024 DOI: 10.1007/978-981-97-6489-1_20
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• Stroke-Sense: A Neural Network for Identifying Four Types of Cricketing Shots
  2023 DOI: 10.1007/978-981-99-3878-0_54
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