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Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...
The inversion of the one-dimensional wave spectrum from dual-polarized synthetic aperture radar (SAR) data is performed using machine learning methods, namely Random Forest (RF), eXtreme Gradient ...
Abstract: The computational complexity of the Transformer model grows quadratically with input sequence length. This causes a sharp increase in computational cost and memory consumption for ...
Abstract: As computer vision and AI technologies advance at an accelerated pace, image processing has permeated critical domains like healthcare diagnostics, surveillance systems, and autonomous ...
Abstract: Multidimensional parameter estimation is a critical challenge in fields such as radar, sonar, and wireless communications, where the space-alternating generalized expectation-maximization ...
Abstract: Identification of PCB board defects early in the manufacturing process is crucial, as PCB quality control plays an important role in the electronics manufacturing industry. Defective PCBs ...
CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
Abstract: Identifying the emotions hidden in speech (SER) encounters difficulties in virtue of the subjective and variable nature of human emotions, along with limitations such as data dependency, ...