| Publications / Journals |
Journal Publications:
- Ranjeet Ranjan Jha, Arvind Muralie, Munish Daroch, Arnav Bhavsar, Aditya Nigam, “Enhancing Autism Spectrum Disorder identification in multi-site MRI imaging: A multi-head cross-attention and multi-context approach for addressing variability in un-harmonized data”, in Artificial Intelligence in Medicine, 2024
- Ranjeet Ranjan Jha, B. V. Rathish Kumar, Sudhir K Pathak, Arnav Bhavsar, Aditya Nigam, “TrGANet: Transforming 3T to 7T dMRI using Trapezoidal Rule and Graph based Attention Modules”, in Medical Image Analysis, 2023
- Ranjeet Ranjan Jha, B. V. Rathish Kumar, Sudhir K Pathak, Walter Schneider, Arnav Bhavsar, Aditya Nigam, “Undersampled Single Shell to MSMT fODF Reconstruction using CNN-based ODE Solver” in Computer Methods and Programs in Biomedicine, 2023
- Ranjeet Ranjan Jha, Sudhir K Pathak, Vishwesh Nath, Walter Schneider, B. V. Rathish Kumar, Arnav Bhavsar, Aditya Nigam, “VRfRNet: Volumetric ROI fODF Reconstruction Network for estimation of Multi-Tissue Constrained Spherical Deconvolution with only Single Shell dMRI” in Magnetic Resonance Imaging Journal, 2022
- Ranjeet Ranjan Jha, Gaurav Jaswal, Arnav Bhavsar, Aditya Nigam, “Single-Shell to Multi-Shell dMRI Transformation using Spatial and Volumetric Multilevel Hierarchical Reconstruction Framework” in Magnetic Resonance Imaging Journal, 2022
- Ranjeet Ranjan Jha, Gaurav Jaswal, Divij, Shrestha and Aditya Nigam, “PixISegNet: Pixel Level Iris Segmentation Network using Convolutional Encoder-Decoder with Stacked Hourglass Bottleneck” in Journal of IET Biometrics, IET, 2019
- Rahul Mishra, Krishan Sharma, Ranjeet Ranjan Jha, Arnav Bhavsar NeuroGAN: Image reconstruction from EEG signals via an attention based GAN in Neural Computing and Applications, 2022
- Sudhir Kumar, Viswanathan Chinnusamy, Tanuj Misra, Alka Arora, Sudeep Marwaha, Ranjeet Ranjan Jha, Mrinmoy Ray and Shailendra Kumar Yield-SpikeSegNet: An Extension of SpikeSegNet Deep-Learning Approach for the Yield Estimation in the Wheat Using Visual Images in Applied Artificial Intelligence, 2022
- Tanuj Misra, Alka Arora, Sudeep Marwaha, Ranjeet Ranjan Jha, Mrinmoy Ray, Eldho Varghese, Sudhir Kumar, Aditya Nigam, Rabi Narayan Sahoo, Viswanathan Chinnusamy, “Web-SpikeSegNet: deep learning framework for recognition and counting of spikes from visual images of wheat plants” in IEEE Access, 2021
- Aman Kamboj, Rajneesh Rani, Aditya Nigam, Ranjeet Ranjan Jha, “PCED-Net: context-aware ear detection network for unconstrained images” in Journal of Pattern Analysis and Applications, 2020
- Tanuj Misra, Alka Arora, Sudeep Marwaha, Viswanathan Chinnusamy, Atmakuri Ramakrishna Rao, Rajni Jain, Rabi Narayan Sahoo, Mrinmoy Ray, Sudhir Kumar, Dhandapani Raju, Ranjeet Ranjan Jha, Aditya Nigam Swati Goel , “SpikeSegNet-a deep learning approach utilizing encoder-decoder network with hourglass for spike segmentation and counting in wheat plant from visual imaging” in Journal of Plant Methods, 2020
Conference Publications:
- Ankita Joshi, Ashutosh Sharma, Anoushkrit Goel, Ranjeet Ranjan Jha, Chirag Ahuja, Arnav Bhavsar, Aditya Nigam, “Tract-RLFormer: A Tract-Specific RL policy based Decoder-only Transformer Network” Accepted in 2024 International Conference on Pattern Recognition (ICPR-2024)
- Anoushkrit Goel, Bipanjit Singh, Ankita Joshi, Ranjeet Ranjan Jha, Chirag Ahuja, Aditya Nigam, Arnav Bhavsar, “TractoEmbed: Modular Multi-level Embedding framework for white matter tract segmentation” Accepted in 2024 International Conference on Pattern Recognition (ICPR-2024)
- Ranjeet Ranjan Jha, Andra Siva Sai Teja, Venkatesh Wadawadagi, Ravindra Babu Tallamraju, “Enhancing Anomaly Detection in Noisy Images: Unleashing the Power of Attention-Aware PDE Constraint Feature Denoiser Module” Accepted in 2024 International Joint Conference on Neural Networks (IJCNN-2024)
- Ranjeet Ranjan Jha, Hritik Gupta, S Pathak, Ankita Joshi, W Schneider, BVR Kumar, A Bhavsar, A Nigam, “PA-GAN: PARALLEL ATTENTION BASED GAN FOR ENHANCEMENT OF FODF” Accepted in 2023 IEEE International Symposium on Biomedical Imaging (ISBI-2023)
- Ranjeet Ranjan Jha, S Pathak, W Schneider, BVR Kumar, A Bhavsar, A Nigam, “LFANet: Transforming 3T single-shell to 7T multi-shell dMRI using deep learning based Leapfrog and Attention” in 2022 IEEE International Symposium on Biomedical Imaging (ISBI-2022)
- Ranjeet Ranjan Jha, A Bhardwaj, D Garg, Arnav Bhavsar, Aditya Nigam, “MHATC: Autism Spectrum Disorder identification utilizing multi-head attention encoder along with temporal consolidation modules” in Annual International Conference of the IEEE Engineering in Medicine Biology Society (EMBC-2022)
- Ranjeet Ranjan Jha, Hritik Gupta, Sudhir Pathak, Walter Schneider, B. V. Rathish Kumar, Arnav Bhavsar, Aditya Nigam, “Enhancing HARDI reconstruction from undersampled data via multi-context and feature inter-dependency GAN” in 2021 IEEE International Symposium on Biomedical Imaging (ISBI-2021)
- Ranjeet Ranjan Jha, Aditya Nigam, Arnav Bhavsar, Sudhir Pathak, Walter Schneider, B. V. Rathish Kumar, “Multi-Shell D-MRI Reconstruction via Residual Learning utilizing Encoder-Decoder Network with Attention (MSR-Net)” in 42nd Annual International Conference of the IEEE Engineering in Medicine Biology Society (EMBC-2020)
- Ranjeet Ranjan Jha, G Jaswal, A Nigam, A Bhavsar, SK Pathak, R Kumar “HLGSNet: Hierarchical and Lightweight Graph Siamese Network with Triplet Loss for fMRI-based Classification of ADHD” in International Joint Conference on Neural Networks (IJCNN-2020)
- Ranjeet Ranjan Jha, Shreyas Patil, Arnav Bhavsar and Aditya Nigam, “FS2Net : Fiber Structural Similarity Network (FS2Net) for Rotation Invariant Brain Tractography Segmentation using Stacked LSTM based Siamese Network” in 18th International Conference on Computer Analysis of Images and Patterns (CAIP-2019), 3-5 September 2019, Salerno, Italy
- Ranjeet Ranjan Jha, Shreyas M. Patil, Daksh Thapar, and Aditya Nigam, “UBSegNet: Unified Biometric ROI Segmentation Network” in 28th Asian Conference on Pattern Recognition (ACPR), Nanjing, China, Nov 26-29, 2017
- Harsh Arora Arora, Ranjeet Ranjan Jha, Kumar Pradeep, “foilNET: A Convolution based Neural Network for Prediction of Pressure Field around Oscillating Airfoils ” in Fluid Mechanics and Fluid Power Conference (FMFP-2020)
- Seema Kumari, Ranjeet Ranjan Jha, Arnav Bhavsar, Aditya Nigam “Indoor–Outdoor Scene Classification with Residual Convolutional Neural Network” in Proceedings of 3rd International Conference on Computer Vision and Image Processing (CVIP-2020)
- Gitika, Ranjeet Ranjan Jha, Kamlesh Tiwari and Aditya Nigam, “SP-NET: One Shot Fingerprint Singular-Point Detector” in 30th British Machine Vision Conference (WS@BMVC-2019), 9-12 September 2019, Cardiff, UK
- Seema Kumari, Ranjeet Ranjan Jha, Arnav Bhavsar and Aditya Nigam, “Autodepth: Single Image Depth Map Estimation via. Residual CNN Encoder-Decoder and Stacked Hourglass” in International Conference on Image Processing (ICIP-2019), 22-25 September 2019, Taipei, Taiwan
- Shreyas Malakarjun Patil, Ranjeet Ranjan Jha, Aditya Nigam, “IpSegNet: deep convolutional neural network based segmentation framework for iris and pupil” in 13th International Conference on Signal-Image Technology Internet-Based Systems (SITIS-2017)
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