Abstract: The recent advancements in the surging field of Deep Learning (DL) have revolutionized every sphere of life, and the healthcare domain is no exception. The enormous success of DL models, ...
Abstract: Extremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth ...
Abstract: Transformer is leading a trend in the field of image processing. While existing lightweight image processing transformers have achieved notable success, they primarily focus on reducing ...
Abstract: Image-based methods have replicated the success from 2-D domain to 3-D point cloud semantic segmentation. However, when we directly apply 2-D techniques to the projected pseudo-image, ...
Abstract: Monitoring building efficiency is a hot topic for engineers and researchers. Thermal infrared (TIR) images describe thermal attributes but require professional knowledge for analysis.
Abstract: Weakly supervised point cloud semantic segmentation methods that require 1% or fewer labels with the aim of realizing almost the same performance as fully supervised approaches have recently ...
Abstract: This article examines the current status of quantum computing (QC) in Earth observation and satellite imagery. We analyze the potential limitations and applications of quantum learning ...
Abstract: The Multiply and Accumulator (MAC) in Convolution Neural Network (CNN) for image applications demands an efficient matrix multiplier. This study presents an area- and power-efficient ...
Image Processing in Python for 3D image stacks, or IMPPY3D, is a software repository comprising mostly Python scripts that simplify post-processing and 3D shape characterization of grayscale image ...
Abstract: Recently, distributed learning approaches have been studied for using data from multiple sources without sharing them, but they are not usually suitable in applications where each client ...
Abstract: The intellectual property of deep networks can be easily “stolen” by surrogate model attack. There has been significant progress in protecting the model IP in classification tasks. However, ...
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