AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...
A Disjoint Samples-Based 3D-CNN With Active Transfer Learning for Hyperspectral Image Classification
Abstract: Convolutional neural networks (CNNs) have been extensively studied for hyperspectral image classification (HSIC). However, CNNs are critically attributed to a large number of labeled ...
Abstract: The global decrease in native pollinators poses a substantial challenge to agricultural production and food security, particularly in malnutrition prone countries. There is a huge potential ...
1 Amazon Web Services, Seattle, USA. 2 Rajiv Gandhi University of Knowledge Technologies, Nuzvid, India. Optical Coherence Tomography (OCT) is a non-invasive imaging modality widely employed for ...
Human inventions, namely engineered systems, have relied on fundamental discoveries in physics and mathematics, e.g., Maxwell’s equations, Quantum mechanics, Information theory, etc., thereby applying ...
fDepartment of Nephrology and Immunology, RWTH Aachen University Hospital, Aachen, Germany gDepartment of Medicine III, RWTH Aachen University Hospital, Aachen, Germany hDepartment of Pathology, ...
Inundation mapping is a critical task for damage assessment, emergency management, and prioritizing relief efforts during a flooding event. Remote sensing has been an effective tool for interpreting ...
This demo shows how to interpret the classification by CNN using LIME (Local Interpretable Model-agnostic Explanations) [1]. This demo was created based on [1], but the implementation might be a ...
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