Abstract: In remote sensing image classification, active learning aims to learn a good classifier as best as possible by choosing the most valuable (informative and representative) training samples.

Tension: We fear direct confrontation but also crave honesty and respect in our interactions. Noise: Conventional wisdom ...

Motivated by this, we propose a deep learning approach for passive beamforming design in RIS-assisted systems. In particular, a customized deep neural network is trained offline using the unsupervised ...

Department of Chemistry, College of Arts and Sciences, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy and Department of Pharmacology, School of Medicine, ...

Additionally, we aimed to develop a predictive model using machine learning techniques to forecast the results ... the remission rate associated with maternal dietary avoidance was 47.38%. The overall ...

A major neuroscience breakthrough has been achieved with the help of an artificial intelligence (AI) deep learning algorithm. In a study published this month in Cell, a multinational team of ...

Normally, when we speak about active and passive investing, we are comparing two highly debated investment strategies. Active investing usually employs a portfolio or money manager that charges a ...

As Indian investors seek optimal strategies for wealth creation in 2025, the debate between active and passive mutual funds remains pivotal. Both approaches offer distinct advantages and challenges, ...