As atmospheric carbon dioxide levels continue to rise, accurately measuring the carbon stored in the world's forests has become more critical than ever. Forests are vital carbon sinks, but traditional ...

Since his return to office, President Trump and his family have engaged in a moneymaking campaign like none in modern American history. A headshot of President Trump sits in the center of a network ...

1 College of Finance and Commerce, Guangzhou Railway Polytechnic, Guangzhou, China. 2 School of Intelligent Construction and Civil Engineering, Zhongyuan University of Technology, Zhengzhou, China. 3 ...

To explain how a convolutional neural network (CNN) processes an image, it is common to generate classification activation maps (CAMs) to reveal image areas that are relevant to output. Nevertheless, ...

Abstract: In this study, we studied unsupervised multiview learning techniques focused on maximizing correlation, particularly Deep Canonically Correlated Autoencoders (DCCAE). The goal of this study ...

With the rapid development of machine learning, Deep Neural Network (DNN) exhibits superior performance in solving complex problems like computer vision and natural language processing compared with ...

Cues predictive of target locations orient covert attention, improving perceptual performance. Studies have focused on attentional influences on neural activity, but how cues activate attention and ...

Species distribution models (SDMs) often overlook critical spatial heterogeneity and multiscale environmental patterns, which limit their predictive accuracy for species occurrences. We demonstrate ...