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Publications
The researchers in our team regularly have their works published in top scientific journals. You'll find our recent publications mentioned here.
1. A Somani, AA Sekh, IS Opstad, AB Birgisdottir, T Myrmel, BS Ahluwalia (2022). Virtual Labeling of Mitochondria in Living Cells using Correlative Imaging and Physics-guided Deep Learning Biomedical Optics Express 10.1364/BOE.464177. (link)
2. Soham Chattopadhyay, Antoni Malachowski, J. K. Swain, R. A. Dalmo, A. Horsch, D. K. Prasad (2022). Mapping functional changes in the embryonic heart of Atlantic salmon post viral infection using AI technique. IEEE International Conference on Image Processing (ICIP).(link)
3. Deepak K Gupta, Udbhav Bamba, Abhishek Thakur, Akash Gupta, Suraj Sharan, Ertugrul Demir, Dilip K Prasad (2022). UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images. arXiv preprint arXiv:2206.12681 (link)
4. Pragyan Banerjee, Shivam Milind Akarte, Prakhar Kumar, Muhammad Shamsuzzaman, Krishna Agarwal, Ankit Butola, Dilip K Prasad, Frank Melandsø, Habib Anowarul (2022). High-resolution imaging in acoustic microscopy using deep learning. (link)
5. D Singh, A Somani, A Horsch, DK Prasad (2022). Counterfactual Explainable Gastrointestinal and Colonoscopy Image Segmentation. International Symposium on Biomedical Imaging (ISBI). (link)
6. Marc Weitz, Shaheen Syed, Laila Arnesdatter Hopstock, Bente Morseth, Dilip Kumar Prasad, Alexander Horsch (2022). Discrimination of sleep and wake periods from a hip-worn raw acceleration sensor using recurrent neural networks. (link)
7. Sumit Rai, Arti Kumari, Dilip K. Prasad (2022). Client Selection in Federated Learning under Imperfections in Environment, AI . (link)
8. Zicheng Liu, Mayank Roy, Dilip K Prasad, Krishna Agarwal (2022). Physics-guided Loss Functions Improve Deep Learning Performance in Inverse Scattering. IEEE Transactions on Computational Imaging. (link)
9. A.A. Sekh, I-S. Opstad, G Godtliebsen, A.B. Birgisdottir, B.S. Ahluwalia, K. Agarwal, D.K. Prasad (2021). Physics based machine learning for sub-cellular segmentation in living cells. Nature Machine Intelligence. (link)
10. S Chattopadhyay, L Zary, C Quek, Dilip K. Prasad (2021). Motivation detection using EEG signal analysis by residual-in-residual convolutional neural network. Expert Systems With Applications. 10.1016/j.eswa.2021.115548 (link)
12. Somani, Ayush & Sk, Arif Ahmed & Opstad, Ida & Birgisdottir, Asa & Myrmel, Truls & Ahluwalia, Balpreet & Agarwal, Krishna & Prasad, Dilip & Horsch, Alexander. (2021). Digital Staining of Mitochondria in Label-free Live-cell Microscopy. 10.1007/978-3-658-33198-6_55. (link)
14. Joshi, Deepa & Butola, Ankit & Kanade, Sheetal & Prasad, Dilip & Sevanthi, Amitha Mithra & Singh, N & Bisht, Deepak & Mehta, Dalip. (2021). Label-free non-invasive classification of rice seeds using optical coherence tomography assisted with deep neural network. Optics & Laser Technology. 137. 10.1016/j.optlastec.2020.106861. (link)
15. Jadhav, Suyog & Acuña M., Sebastian & Opstad, Ida & Ahluwalia, Balpreet & Agarwal, Krishna & Prasad, Dilip. (2021). Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning. Biomedical Optics Express. 12. 191. 10.1364/BOE.410617.
16. Zhe, Quah & Sk, Arif Ahmed & Quek, Chai & Prasad, Dilip. (2021). Recurrent Self-evolving Takagi–Sugeno–Kan Fuzzy Neural Network (RST-FNN) Based Type-2 Diabetic Modeling. 10.1007/978-3-030-74826-5_11. (link)
17. Jun, Seow & Sk, Arif Ahmed & Quek, Chai & Prasad, Dilip. (2021). seMLP: Self-evolving Multi-layer Perceptron in Stock Trading Decision Making. SN Computer Science. 2. 10.1007/s42979-021-00524-9. (link)
18. Liu, Feng & Sk, Arif Ahmed & Quek, Chai & Ng, Geok & Prasad, Dilip. (2021). RS-HeRR: a rough set-based Hebbian rule reduction neuro-fuzzy system. Neural Computing and Applications. 33. 10.1007/s00521-020-04997-2.
19. Ströhl, Florian & Jadhav, Suyog & Ahluwalia, Balpreet & Agarwal, Krishna & Prasad, Dilip. (2020). Object detection neural network improves Fourier ptychography reconstruction. Optics Express. 28. 37199. 10.1364/OE.409679.
13. Hui Xue, Bjørn-Morten Batalden, Puneet Sharma, Jarle André Johansen, Dilip K. Prasad. (2021). Applied Sciences. Biosignals based driving skill classification using machine learning: a case study of maritime navigation. 10.3390/app11209765 (link)
24. A Singh, A Bhave, Dilip K Prasad (2020). Single image dehazing for a variety of haze scenarios using back projected pyramid network. European Conference on Computer Vision Workshops.
25. A. A Sekh, I-S. Opstad, AB Birgisdottir, T Myrmel, BS Ahluwalia, K Agarwal, Dilip K Prasad (2020). Learning nanoscale motion patterns of vesicles in living cells. IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
26. Ratnabali Pal, Arif Ahmed Sekh, Samarjit Kar, Dilip K Prasad (2020). Neural network based country wise risk prediction of COVID-19. Applied Science. /10.3390/app10186448
28. Ankit Butola, Dilip K Prasad, Azeem Ahmad, Vishesh Dubey, Darakhshan Qaiser, Anurag Srivastava, Paramsivam Senthilkumaran, Balpreet Singh Ahluwalia, Dalip Singh Mehta (2020). Deep learning architecture LightOCT for diagnostic decision support using optical coherence tomography images of biological samples. Biomedical Optics Express 10.1364/BOE.395487
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