Search Results for author: Viksit Kumar

Found 4 papers, 0 papers with code

Network-Agnostic Knowledge Transfer for Medical Image Segmentation

no code implementations23 Jan 2021 Shuhang Wang, Vivek Kumar Singh, Alex Benjamin, Mercy Asiedu, Elham Yousef Kalafi, Eugene Cheah, Viksit Kumar, Anthony Samir

The salient features of our algorithm include: 1)no need for original training data or generative networks, 2) knowledge transfer between different architectures, 3) ease of implementation for downstream tasks by using the downstream task dataset as the transferal dataset, 4) knowledge transfer of an ensemble of models, trained independently, into one student model.

Knowledge Distillation Medical Image Segmentation +1

Network-Agnostic Knowledge Transfer from Latent Dataset for Medical Image Segmentation

no code implementations1 Jan 2021 Shuhang Wang, Eugene Cheah, Elham Yousef Kalafi, Mercy Asiedu, Alex Benjamin, Vivek Kumar Singh, Ge Zhang, Viksit Kumar, Anthony Edward Samir

Transfer learning often employs all or part of the weights of a pre-trained net-work to the problem at hand; this limits the flexibility of new neural architectures.

Medical Image Segmentation Transfer Learning

Weakly Supervised Context Encoder using DICOM metadata in Ultrasound Imaging

no code implementations20 Mar 2020 Szu-Yeu Hu, Shuhang Wang, Wei-Hung Weng, JingChao Wang, XiaoHong Wang, Arinc Ozturk, Qian Li, Viksit Kumar, Anthony E. Samir

Modern deep learning algorithms geared towards clinical adaption rely on a significant amount of high fidelity labeled data.

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