B Bhattarai MultiModal Learning Lab (MMLL)

B Bhattarai MultiModal Learning Lab (MMLL) is a research group within NAAMII that focuses on theoretical and applied research in Machine learning (ML) where the researches process information from heterogeneous sources such as vision, text, and speech to make computers understand, interpret and reason. Our applications include but are not limited to computer vision, medical image analysis and low-resource language processing.

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Bidur Khanal, Tianhong Dai, Binod Bhattarai, Cristian Linte
Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise
MICCAI, 2024
Bibtex

@article{khanal2024active,
  title={Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise},
  author={Khanal, Bidur and Dai, Tianhong and Bhattarai, Binod and Linte, Cristian},
  journal={arXiv preprint arXiv:2407.05973},
  year={2024}
}

Sanskar Amgain, Prashant Shrestha, Sophia Bano, Ignacio del Valle Torres, Michael Cunniffe, Victor Hernandez, Phil Beales, Binod Bhattarai
Investigation of Federated Learning Algorithms for Retinal Optical Coherence Tomography Image Classification with Statistical Heterogeneity
IPCAI, 2024
Bibtex

@article{amgain2024investigation,
  title={Investigation of Federated Learning Algorithms for Retinal Optical Coherence Tomography Image Classification with Statistical Heterogeneity},
  author={Amgain, Sanskar and Shrestha, Prashant and Bano, Sophia and Torres, Ignacio del Valle and Cunniffe, Michael and Hernandez, Victor and Beales, Phil and Bhattarai, Binod},
  journal={arXiv preprint arXiv:2402.10035},
  year={2024}
}

CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing Modalities
International Conference on Medical Image Computing and Computer-Assisted Intervention(MICCAI), 2024
Bibtex

@article{poudel2024car,
  title={CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing Modalities},
  author={Poudel, Pranav and Shrestha, Prashant and Amgain, Sanskar and Shrestha, Yash Raj and Gyawali, Prashnna and Bhattarai, Binod},
  journal={arXiv preprint arXiv:2407.08648},
  year={2024}
}

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