Browsing Division of Interdisciplinary Research by Subject "Deep learning"
Now showing items 1-4 of 4
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Improving photoacoustic imaging with model compensating and deep learning methods
Photoacoustic imaging is a hybrid biomedical imaging technique combining optical ab- sorption contrast with ultrasonic resolution. It is a non-invasive technique that is scalable to reveal structural, functional, and ... -
Mitigating Domain Shift via Self-training in Single and Multi-target Unsupervised Domain Adaptation
Though deep learning has achieved significant successes in many computer vision tasks, the state-of-the-art approaches rely on the availability of a large amount of labeled data for supervision, collection of which is ... -
Quantifying the past and future variability in the Bay of Bengal using statistical and deep learning methods
The Bay of Bengal, the world's largest bay, along with the Andaman Sea, a peripheral sea situated in the southeastern part of the bay, is crucial to the economic and maritime security of India. Understanding the dynamics ... -
Unsupervised Test-time Adaptation for Patient-Specific Deep Learning Models in Medical Imaging
Deep learning (DL) models have achieved state-of-the-art results in multiple medical imaging applications, resulting in the widespread adoption of artificial intelligence (AI) models for radiological workflows. Despite ...