UBSegNet: Unified Biometric Region of Interest Segmentation Network. - Ranjeet Ranjan Jha; Daksh Thapar; Shreyas Malakarjun Patil; Aditya Nigam (ACPR, 2017)

IPSegNet : Deep Convolutional Neural Network Based Segmentation Framework for Iris and Pupil. - Shreyas Malakarjun Patil; Ranjeet Ranjan Jha; Aditya Nigam (SITIS, 2017)

Indoor-Outdoor Scene Classification with Residual Convolutional Neural Network. - Seema Kumari; Ranjeet Ranjan Jha; Arnav Bhavsar; Aditya Nigam (CVIP (2), 2018)

FS2Net: Fiber Structural Similarity Network (FS2Net) for Rotation Invariant Brain Tractography Segmentation Using Stacked LSTM Based Siamese Network. - Ranjeet Ranjan Jha; Shreyas Malakarjun Patil; Aditya Nigam; Arnav Bhavsar (CAIP (2), 2019)

AUTODEPTH: Single Image Depth Map Estimation via Residual CNN Encoder-Decoder and Stacked Hourglass. - Seema Kumari; Ranjeet Ranjan Jha; Arnav Bhavsar; Aditya Nigam (ICIP, 2019)

SP-NET: One Shot Fingerprint Singular-Point Detector. - Geetika Arora; Ranjeet Ranjan Jha; Akash Agrawal; Kamlesh Tiwari; Aditya Nigam (CoRR, 2019)

Multi-Shell D-MRI Reconstruction via Residual Learning utilizing Encoder-Decoder Network with Attention (MSR-Net). - Ranjeet Ranjan Jha; Aditya Nigam; Arnav Bhavsar; Sudhir K. Pathak; Walter Schneider; Rathish Kumar (EMBC, 2020)

HLGSNet: Hierarchical and Lightweight Graph Siamese Network with Triplet Loss for fMRI-based Classification of ADHD. - Ranjeet Ranjan Jha; Aditya Nigam; Arnav Bhavsar; Gaurav Jaswal; Sudhir K. Pathak; Rathish Kumar (IJCNN, 2020)

UESegNet: Context Aware Unconstrained ROI Segmentation Networks for Ear Biometric. - Aman Kamboj; Rajneesh Rani; Aditya Nigam; Ranjeet Ranjan Jha (CoRR, 2020)

PixISegNet: pixel-level iris segmentation network using convolutional encoder-decoder with stacked hourglass bottleneck. - Ranjeet Ranjan Jha; Gaurav Jaswal; Divij Gupta; Shreshth Saini; Aditya Nigam (IET Biom., 2020)

Enhancing HARDI Reconstruction from Undersampled Data Via Multi-Context and Feature Inter-Dependency GAN. - Ranjeet Ranjan Jha; Hritik Gupta; Sudhir K. Pathak; Walter Schneider; B. V. Rathish Kumar; Arnav Bhavsar; Aditya Nigam (ISBI, 2021)

Web-SpikeSegNet: Deep Learning Framework for Recognition and Counting of Spikes From Visual Images of Wheat Plants. - Tanuj Misra; Alka Arora; Sudeep Marwaha; Ranjeet Ranjan Jha; Mrinmoy Ray; Rajni Jain; Atmakuri Ramakrishna Rao; Eldho Varghese; Shailendra Kumar; Sudhir Kumar 003; Aditya Nigam; Rabi Narayan Sahoo; et al. (IEEE Access, 2021)

CED-Net: context-aware ear detection network for unconstrained images. - Aman Kamboj; Rajneesh Rani; Aditya Nigam; Ranjeet Ranjan Jha (Pattern Anal. Appl., 2021)

MHATC: Autism Spectrum Disorder Identification Utilizing Multi-Head Attention Encoder Along with Temporal Consolidation Modules. - Ranjeet Ranjan Jha; Abhishek Bhardwaj; Devin Garg; Arnav Bhavsar; Aditya Nigam (EMBC, 2022)

LFANET: Transforming 3T Single-Shell to 7T Multi-Shell DMRI Using Deep Learning Based Leapfrog and Attention. - Ranjeet Ranjan Jha; Sudhir K. Pathak; Walter Schneider; B. V. Rathish Kumar; Arnav Bhavsar; Aditya Nigam (ISBI, 2022)

Yield-SpikeSegNet: An Extension of SpikeSegNet Deep-Learning Approach for the Yield Estimation in the Wheat Using Visual Images. - Tanuj Misra; Alka Arora; Sudeep Marwaha; Ranjeet Ranjan Jha; Mrinmoy Ray; Shailendra Kumar; Sudhir Kumar 003; Viswanathan Chinnusamy (Appl. Artif. Intell., 2022)

PA-GAN: Parallel Attention Based Gan for Enhancement of FODF. - Ranjeet Ranjan Jha; Hritik Gupta; Sudhir K. Pathak; Ankita Joshi; Walter Schneider; B. V. Rathish Kumar; Arnav Bhavsar; Aditya Nigam (ISBI, 2023)

TrGANet: Transforming 3T to 7T dMRI using Trapezoidal Rule and Graph based Attention Modules. - Ranjeet Ranjan Jha; B. V. Rathish Kumar; Sudhir K. Pathak; Arnav Bhavsar; Aditya Nigam (Medical Image Anal., 2023)

Undersampled single-shell to MSMT fODF reconstruction using CNN-based ODE solver. - Ranjeet Ranjan Jha; B. V. Rathish Kumar; Sudhir K. Pathak; Walter Schneider; Arnav Bhavsar; Aditya Nigam (Comput. Methods Programs Biomed., 2023)

NeuroGAN: image reconstruction from EEG signals via an attention-based GAN. - Rahul Mishra 005; Krishan Sharma; Ranjeet Ranjan Jha; Arnav Bhavsar (Neural Comput. Appl., 2023)

TractoEmbed: Modular Multi-level Embedding Framework for White Matter Tract Segmentation. - Anoushkrit Goel; Bipanjit Singh; Ankita Joshi; Ranjeet Ranjan Jha; Chirag Ahuja; Aditya Nigam; Arnav Bhavsar (ICPR (28), 2024)

Tract-RLFormer: A Tract-Specific RL Policy Based Decoder-Only Transformer Network. - Ankita Joshi; Ashutosh Sharma; Anoushkrit Goel; Ranjeet Ranjan Jha; Chirag Kamal Ahuja; Arnav Bhavsar; Aditya Nigam (ICPR (13), 2024)

Enhancing Anomaly Detection in Noisy Images: Unleashing the Power of Attention-Aware PDE Constraint Feature Denoiser Module. - Ranjeet Ranjan Jha; Andra Siva Sai Teja; Venkatesh Wadawadagi; Ravindra Babu Tallamraju (IJCNN, 2024)

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. - Ranjeet Ranjan Jha; Arvind Muralie; Munish Daroch; Arnav Bhavsar; Aditya Nigam (Artif. Intell. Medicine, 2024)

Fortifying Federated Learning Towards Trustworthiness via Auditable Data Valuation and Verifiable Client Contribution. - K. Naveen Kumar; Ranjeet Ranjan Jha; C. Krishna Mohan; Ravindra Babu Tallamraju (CVPR, 2025)

Tractogpt: A GPT Architecture for White Matter Tract Segmentation. - Anoushkrit Goel; Simroop Singh; Ankita Joshi; Ranjeet Ranjan Jha; Chirag Ahuja; Aditya Nigam; Arnav Bhavsar (ISBI, 2025)

TractoGPT: A GPT architecture for White Matter Segmentation. - Anoushkrit Goel; Simroop Singh; Ankita Joshi; Ranjeet Ranjan Jha; Chirag Ahuja; Aditya Nigam; Arnav Bhavsar (CoRR, 2025)