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Browsing by Subject "Transfer learning"

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DeepDeMod: BPSK demodulation using deep learning over software-defined radio

Ahmad, A.; Agarwal, S.; Darshi, S.; Chakravarty, S. (2022-12-09)

In wireless communication, signal demodulation under non-ideal conditions is one of the important research topic. In this paper, a novel non-coherent binary phase shift keying demodulator based on deep neural network, ...
Faster fog computing based over-the-air vehicular updates: a transfer learning approach

Maruf, M. A.; Singh, A.; Azim, A.; Auluck, N. (2021-10-24)

Fog computing is a promising option for time sensitive vehicular over-the-air (OTA) updates, as it can offer enhanced network durability and lower communication delays, as compared to the cloud. Fog node utilization for ...
Label space driven feature space remapping

Sukhija, S. (2018-11-13)

The elicitation of labeled training data from physical sources is a primary bottleneck that limits the applicability of traditional supervised learning algorithms. Transfer learning algorithms overcome the limitation ...
Multi-site FMRI data normalization to reduce inter-scanner variability of activation

Thomas, A.J. (2018-10-09)

Since the introduction of functional Magnetic Resonance Imaging (fMRI), a non invasive technique for mapping the brain activity, there has been an exponential growth in the brain mapping studies. Recently, multi-center ...
Supervised heterogeneous transfer learning using random forests

Sukhija, S.; Krishnan, N.C.; Kumar, D. (2018-12-20)

Supervised transfer learning algorithms utilize labeled data from auxiliary domains for learning in another domain where labeled data is scarce or absent. Given sufficient cross-domain corresponding instances, one can ...
Understanding calibration of deep neural networks for medical image classification

Sambyal, A S; Niyaz, U; Krishnan, N C.; Bathula, D R. (2024-05-08)

Abstract: Background and Objective – In the field of medical image analysis, achieving high accuracy is not enough; ensuring well-calibrated predictions is also crucial. Confidence scores of a deep neural network play a ...

Now showing items 1-6 of 6

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