Tajbakhsh, Nima

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

Tajbakhsh, N., Shin, J. Y., Gurudu, S. R., Hurst, R. T., Kendall, C. B., Gotway, M. B., & Liang, J. (2016) · IEEE Transactions on Medical Imaging

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 3,277

Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation

Tajbakhsh, N., Jeyaseelan, L., Li, Q., Chiang, J. N., Wu, Z., & Ding, X. (2020) · Medical Image Analysis

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 1,095

StarCoder 2 and The Stack v2: The Next Generation

Lozhkov, A., Li, R., Allal, L. B., Cassano, F., Lamy-Poirier, J., Tazi, N., Tang, A., Pykhtar, D., Liu, J., Wei, Y., et al. (2024) · arXiv

Software Engineering ResearchTopic Modeling

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Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models

NVIDIA, :, Blakeman, A., Basant, A., Khattar, A., Renduchintala, A., Bercovich, A., Ficek, A., Bjorlin, A., Taghibakhshi, A., et al. (2025) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

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