This article presents a new method for multiview clustering (MVC) via contrastive learning, called CCEC. MVC is a process that groups data samples into clusters by synthesizing information across multiple…
Continue readingThe article discusses the use of Physics-Informed Neural Networks (PINNs) for solving partial differential equations (PDEs). However, PINNs can face difficulties when dealing with equations with rapidly changing solutions. To…
Continue readingThis research aims to improve the prediction of travelers’ next destinations by using a novel model architecture based on Long Short-Term Memory (LSTM). This approach is particularly useful in the…
Continue readingThe article presents a survey on transfer learning methods applied in the field of Human Activity Recognition (HAR). The authors highlight the challenges faced in sensor-based HAR due to the…
Continue readingThe paper investigates the challenge of recognizing distinct arm movements of robots in noisy environments using machine learning techniques. A vision system tracks the robot’s movements, and a deep learning…
Continue readingThe paper discusses the development of A-KIT, an adaptive Kalman-informed transformer, designed to improve the accuracy of sensor fusion in navigation applications. Traditional methods, such as the extended Kalman filter…
Continue readingThe paper introduces an enhanced automated quality assessment network (IBS-AQSNet), a new method for assessing the quality of interactive building segmentation in high-resolution remote sensing imagery. The system combines a…
Continue readingThe research introduces the Continuous Time Continuous Space Homeostatic Regulated Reinforcement Learning (CTCS-HRRL) framework. This framework extends the Homeostatic Regulated Reinforcement Learning (HRRL) framework to a continuous time-space environment. The…
Continue readingSmart Grid networks, which rely on advanced technologies for energy generation, distribution, and consumption, are increasingly susceptible to cyber-attacks. This paper surveys the role of Deep Learning (DL) in enhancing…
Continue readingThe article introduces ConKeD, a novel deep learning approach for Retinal Image Registration (RIR). Unlike existing methods, ConKeD uses a multi-positive multi-negative contrastive learning strategy to utilize additional information from…
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