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Data-efficient Deep Learning Algorithms for Computer Vision Applications
The performance of any deep learning model depends heavily on the quantity and quality of the available training data. The generalization of the trained deep models improves with the availability of a large number of ...
Development of Novel Deep Learning Models with Improved Generalizability for Medical Image Analysis
Medical imaging is a process of visualization of disease/tissue in a non-invasive manner. Several imaging techniques like computed tomography (CT), magnetic resonance imaging (MRI), optical coherence tomography (OCT), and ...
Sparsification of Reaction-Diffusion Dynamical Systems on Complex Networks
Graph sparsification is an area of interest in computer science and applied mathematics. Spar-
sification of a graph, in general, aims to reduce the number of edges in the network while
preserving specific properties of ...
An arbitrary lagrangian eulerian volume of fluid method for floating body dynamics simulation
The floating body dynamics is treated as a Fluid-Structure Interaction (FSI) problem. A FSI problem is where the forces from the fluid move/deform the interacting structure, and the movement of the structure, in turn, ...
Intelligent Methods for Cloud Workload Orchestration in Data Centers
Cloud workload orchestration plays a pivotal role in optimizing the performance, resource utilization, and cost effectiveness of applications in data centers. As modern businesses and IT operations are migrating their ...