Dilip K. Prasad



  • Pragyan Banerjee, Shivam Milind Akarte, Prakhar Kumar, Muhammad Shamsuzzaman, Ankit Butola, Krishna Agarwal et al.:
    High-resolution imaging in acoustic microscopy using deep learning
    Machine Learning: Science and Technology 2024 DOI
  • Abhinanda Ranjit Punnakkal, Suyog Sakhahari Jadhav, Krishna Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    MiShape: 3D Shape Modelling of Mitochondria in Microscopy
    arXiv.org 2023 DOI
  • Rohit Agarwal, Ankit Butola, Ludwig Alexander Horsch, Dilip Kumar Prasad, Krishna Agarwal :
    Taxonomy of hybridly polarized Stokes vortex beams
    arXiv.org 2023 DOI
  • Momojit Biswas, Himanshu Buckchash, Dilip Kumar Prasad :
    pNNCLR: Stochastic Pseudo Neighborhoods for Contrastive Learning based Unsupervised Representation Learning Problems
    arXiv.org 2023 DOI
  • Ayush Singh, Yash Bhambhu, Himanshu Buckchash, Deepak Gupta, Dilip Kumar Prasad :
    Latent Graph Attention for Enhanced Spatial Context
    arXiv.org 2023 DOI
  • Rohit Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Modelling Irregularly Sampled Time Series Without Imputation
    arXiv.org 2023 DOI
  • Abhinanda Ranjit Punnakkal, Gustav Godtliebsen, Ayush Somani, Sebastian Andres Acuna Maldonado, Åsa birna Birgisdottir, Dilip K. Prasad et al.:
    Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
    Journal of Visualized Experiments 2023 ARKIV / DOI
  • Gustav Godtliebsen, Kenneth Bowitz Larsen, Zambarlal Babanrao Bhujabal, Ida Sundvor Opstad, Mireia Nager Grifo, Abhinanda Ranjit Punnakkal et al.:
    High-resolution visualization and assessment of basal and OXPHOS-induced mitophagy in H9c2 cardiomyoblasts
    Autophagy 2023 ARKIV / DOI
  • Ayush Somani, Pragyan Banerjee, Manu Rastogi, Anowarul Habib, Krishna Agarwal, Dilip Kumar Prasad :
    Image Inpainting With Hypergraphs for Resolution Improvement in Scanning Acoustic Microscopy
    IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2023 FULLTEKST / DOI
  • Rohit Agarwal, Gyanendra Das, Saksham Aggarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Mabnet: Master Assistant Buddy Network With Hybrid Learning for Image Retrieval
    Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2023 DOI
  • Ayush Somani, Pragyan Banerjee, Manu Rastogi, Anowarul Habib, Krishna Agarwal, Dilip Kumar Prasad :
    Image Inpainting With Hypergraphs for Resolution Improvement in Scanning Acoustic Microscopy
    IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2023 ARKIV
  • Rohit Agarwal, Dilip Kumar Prasad, Ludwig Alexander Horsch, Deepak Kumar Gupta :
    Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts
    Transactions on Machine Learning Research (TMLR) 2023
  • Sunil Bhatt, Ankit Butola, Anand Kumar, Pramila Thapa, Akshay Joshi, Suyog S. Jadhav et al.:
    Single-shot multispectral quantitative phase imaging of biological samples using deep learning
    Applied Optics 2023 ARKIV / DOI
  • Xinqiang Chen, Xingyu Wu, Dilip K. Prasad, Bing Wu, Octavian Postolache, Yongsheng Yang :
    Pixel-Wise Ship Identification From Maritime Images via a Semantic Segmentation Model
    IEEE Sensors Journal 2022 DOI
  • S Chattopadhyay, Antoni Malachowski, Jaya Kumari Swain, Roy Ambli Dalmo, Alexander Horsch, Dilip K. Prasad :
    Mapping Functional Changes in the Embryonic Heart of Atlantic Salmon Post Viral Infection Using AI Technique
    Proceedings of IEEE International Conference on Image Processing 2022 DOI
  • Chen Xie, Deepu Rajan, Dilip K. Prasad, Chai Quek :
    An embedded deep fuzzy association model for learning and explanation
    Applied Soft Computing 2022 DOI
  • Ayush Somani, Arif Ahmed Sekh, Ida Sundvor Opstad, Åsa birna Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia et al.:
    Virtual labeling of mitochondria in living cells using correlative imaging and physics-guided deep learning
    Biomedical Optics Express 2022 ARKIV / DOI
  • Zicheng Liu, Mayank Roy, Dilip K. Prasad, Krishna Agarwal :
    Physics-Guided Loss Functions Improve Deep Learning Performance in Inverse Scattering
    IEEE Transactions on Computational Imaging 2022 ARKIV / DOI
  • Divij Singh, Ayush Somani, Alexander Horsch, Dilip K. Prasad :
    Counterfactual Explainable Gastrointestinal and Colonoscopy Image Segmentation
    IEEE International Symposium on Biomedical Imaging 2022 ARKIV / DOI
  • Huixu Dong, Jiadong Zhou, Chen Qiu, Dilip K. Prasad, I-Ming Chen :
    Robotic Manipulations of Cylinders and Ellipsoids by Ellipse Detection With Domain Randomization
    IEEE/ASME transactions on mechatronics 2022 DOI
  • Sumit Rai, Arti Kumari, Dilip K. Prasad :
    Client Selection in Federated Learning under Imperfections in Environment
    AI 2022 ARKIV / DOI
  • S.W Jun, Arif Ahmed Sekh, Chai Quek, Dilip K. Prasad :
    seMLP: Self-evolving Multi-layer Perceptron in Stock Trading Decision Making
    SN Computer Science 2021 ARKIV / DOI
  • Ayush Somani, Divij Singh, Alexander Horsch, Dilip K. Prasad :
    T-MIS: Transparency Adaptation in Medical Image Segmentation
    Nordic Machine Intelligence (NMI) 2021 DOI
  • Arif Ahmed Sekh, Ida Sundvor Opstad, Gustav Godtliebsen, Åsa Birna Birgisdottir, Balpreet Singh Ahluwalia, Krishna Agarwal et al.:
    Physics-based machine learning for subcellular segmentation in living cells
    Nature Machine Intelligence 2021 ARKIV / DOI
  • Deepa Joshi, Ankit Butola, Sheetal Raosaheb Kanade, Dilip K. Prasad, Mithra Amitha Mithra, N.K. Singh et al.:
    Label-free non-invasive classification of rice seeds using optical coherence tomography assisted with deep neural network
    Optics and Laser Technology 2021 ARKIV / DOI
  • Jeow Li Huan, Arif Ahmed Sekh, Chai Quek, Dilip K. Prasad :
    Emotionally charged text classification with deep learning and sentiment semantic
    Neural Computing & Applications 2021 ARKIV / DOI
  • Hui Xue, Bjørn-Morten Batalden, Puneet Sharma, Jarle André Johansen, Dilip K. Prasad :
    Biosignal-Based Driving Skill Classification Using Machine Learning: A Case Study of Maritime Navigation
    Applied Sciences 2021 ARKIV / DOI
  • Suyog Jadhav, Sebastian Andres Acuña Maldonado, Ida Sundvor Opstad, Balpreet Singh Ahluwalia, Krishna Agarwal, Dilip K. Prasad :
    Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning
    Biomedical Optics Express 2021 ARKIV / DOI
  • Huixu Dong, Dilip K. Prasad, I-Ming Chen :
    Object Pose Estimation via Pruned Hough Forest with Combined Split Schemes for Robotic Grasp
    IEEE Transactions on Automation Science and Engineering 2021 DOI
  • Pranab Kanti Roy, Hiranmoy Mondal, Ashis Mallick, Dilip K. Prasad :
    Inverse and efficiency of heat transfer convex fin with multiple nonlinearities
    Heat Transfer 2021 ARKIV / DOI
  • Soham Chattopadhyay, Laila Zary, Chai Quek, Dilip K. Prasad :
    Motivation detection using EEG signal analysis by residual-in-residual convolutional neural network
    Expert Systems With Applications 2021 ARKIV / DOI
  • Ratnabali Pal, Arif Ahmed Sekh, Debi Prosad Dogra, Samarjit Kar, Partha Pratim Roy, Dilip K. Prasad :
    Topic-based Video Analysis: A Survey
    ACM Computing Surveys 2021 FULLTEKST / ARKIV / DOI
  • Ayush Somani, Arif Ahmed Sekh, Ida Sundvor Opstad, Åsa Birna Birgisdottir, Truls Myrmel, Balpreet Singh Ahluwalia et al.:
    Digital Staining of Mitochondria in Label-free Live-cell Microscopy
    Springer 2021 DOI
  • Q.E. Zhe, Arif Ahmed Sekh, Chai Quek, Dilip K. Prasad :
    Recurrent Self-evolving Takagi–Sugeno–Kan Fuzzy Neural Network (RST-FNN) based Type-2 Diabetic Modeling
    Springer 2021 DOI
  • Feng Liu, Arif Ahmed Sekh, Chai Quek, Geok See Ng, Dilip K. Prasad :
    RS-HeRR: a rough set-based Hebbian rule reduction neuro-fuzzy system
    Neural Computing & Applications 2020 ARKIV / DOI
  • Mohammad Ashrafi, Dilip K. Prasad, Chai Quek :
    IT2-GSETSK: An evolving interval Type-II TSK fuzzy neural system for online modeling of noisy data
    Neurocomputing 2020 ARKIV / DOI
  • Florian Ströhl, Suyog Jadhav, Balpreet Singh Ahluwalia, Krishna Agarwal, Dilip K. Prasad :
    Object detection neural network improves Fourier ptychography reconstruction
    Optics Express 2020 ARKIV / DOI
  • Ankit Butola, Daria Popova, Dilip K. Prasad, Azeem Ahmad, Anowarul Habib, Jean-Claude Tinguely et al.:
    High spatially sensitive quantitative phase imaging assisted with deep neural network for classification of human spermatozoa under stressed condition
    Scientific Reports 04. Aug 2020 ARKIV / DOI
  • Nirwan Banerjee, Samir Malakar, Deepak Kumar Gupta, Alexander Horsch, Dilip Kumar Prasad :
    Guided U-Net Aided Efficient Image Data Storing with Shape Preservation
    Springer 2023
  • Ayush Somani, Alexander Horsch, Dilip K. Prasad :
    Interpretability in Deep Learning
    Springer 2023
  • Rohit Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Code - Modelling Irregularly Sampled Time Series Without Imputation
    2023
  • Rohit Agarwal, Ludwig Alexander Horsch, Dilip Kumar Prasad :
    Code - MABNET: Master Assistant Buddy Network for Image Retrieval
    2023
  • Huixu Dong, Jiadong Zhou, Chen Qiu, Dilip K. Prasad, I-Ming Chen :
    Learning-Based Ellipse Detection for Robotic Grasps of Cylinders and Ellipsoids
    2022
  • Xinqiang Chen, Xingyu Wu, Dilip K. Prasad, Bing Wu, Octavian Postolache, Yongsheng Yang :
    Corrections: Pixel-wise ship identification from maritime images via a semantic segmentation model (IEEE Sensors Journal (2022) 22:18 (18180-18191) DOI: 10.1109/JSEN.2022.3195959)
    IEEE Sensors Journal 2022 DOI
  • Rohit Agarwal, Krishna Agarwal, Alexander Horsch, Dilip K. Prasad :
    Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs
    2022 ARKIV
  • Divij Singh, Ayush Somani, Alexander Horsch, Dilip K. Prasad :
    Performance improvement in deep learning models for outdoor semantic segmentation for autonomous driving for unstructured environment
    2021
  • Dilip K. Prasad :
    Physics based AI - 101
    2021
  • Dilip K. Prasad :
    Performing physics-based AI for ground truth hard sub-cellular organelle segmentation using simulated expert
    2021
  • SW Pang, Chai Quek, Dilip K. Prasad :
    GEMM-eMFIS (FRI/E): A Novel General Episodic Memory Mechanism for Fuzzy Neural Networks
  • Ayush Singh, Ajay Bhave, Dilip K. Prasad :
    Single image dehazing for a variety of haze scenarios using back projected pyramid network
    2020 ARKIV

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