Journal of neurophysiology
Sep 28, 2022
Machine-learning systems that classify electroencephalography (EEG) data offer important perspectives for the diagnosis and prognosis of a wide variety of neurological and psychiatric conditions, but their clinical adoption remains low. We propose he...
Computer methods and programs in biomedicine
Sep 28, 2022
BACKGROUND AND OBJECTIVE: Deep learning techniques are powerful tools for image analysis. However, the lack of programming experience makes it difficult for novice users to apply this technology. This project aims to lower the barrier for clinical us...
Medical & biological engineering & computing
Sep 28, 2022
Accurate lung tumor segmentation has great significance in the treatment planning of lung cancer. However, robust lung tumor segmentation becomes challenging due to the heterogeneity of tumors and the similar visual characteristics between tumors and...
Sensors (Basel, Switzerland)
Sep 28, 2022
In general, most of the existing convolutional neural network (CNN)-based deep-learning models suffer from spatial-information loss and inadequate feature-representation issues. This is due to their inability to capture multiscale-context information...
Sensors (Basel, Switzerland)
Sep 28, 2022
The robotics field has been deeply influenced by the advent of deep learning. In recent years, this trend has been characterized by the adoption of large, pretrained models for robotic use cases, which are not compatible with the computational hardwa...
Sensors (Basel, Switzerland)
Sep 28, 2022
Compressed ultrafast photography (CUP) is a type of two-dimensional (2D) imaging technique to observe ultrafast processes. Intelligence reconstruction methods that influence the imaging quality are an essential part of a CUP system. However, existing...
Sensors (Basel, Switzerland)
Sep 28, 2022
The ability to monitor mental effort during a task using a wearable sensor may improve productivity for both work and study. The use of the electrodermal activity (EDA) signal for tracking mental effort is an emerging area of research. Through analys...
Journal of environmental and public health
Sep 28, 2022
The governance of cross-border data flows around the digital economy, data security, and data sovereignty has become a crucial global governance issue. This paper evaluates the legitimacy of data exit rules of CPTPP countries based on machine learnin...
Journal of environmental and public health
Sep 28, 2022
Applicability of statistical models in predicting chlorine decay remains minimally explored. This study predicted residual chlorine using six deep learning and nine machine learning techniques. Suitability of multimodel ensembles (MMEs) including ari...
Journal of environmental and public health
Sep 28, 2022
With the progress of science and technology and the arrival of the big data era, people increasingly rely on computers to deal with daily life and related affairs. In recent years, machine learning has become more and more popular and has achieved go...