Results 71 to 80 of about 497,808 (317)

Threshold Values of Sleep Spindles Features in Healthy Adults Using Scalp‐EEG and Associations With Sleep Parameters

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Sleep spindles are an electrophysiological fingerprint of the sleeping human brain. They can be described in terms of duration, frequency, amplitude, and density, and vary widely according to age and sex. Spindles play a role in sleep and wake functions and are altered in several neurological and psychiatric disorders.
Julien Coelho, Heloïse Degros, Jean‐Arthur Micoulaud‐Franchi, Patricia Sagaspe, Emmanuel d'Incau, Paul Galvez, Christian Berthomier, Pierre Philip, Jacques Taillard   +8 more
wiley   +1 more source

Temporal-Spatial Traffic Flow Prediction Model Based on Prompt Learning

ISPRS International Journal of Geo-Information
Traffic flow prediction is one of the most important and attractive topics in geographical information science (GIS), traffic management, and logistics.
Siteng Cai, Gang Liu, Jing He, Yulun Du, Zhichao Si, Yunhao Jiang   +5 more
doaj   +1 more source

Neural Point Process for Learning Spatiotemporal Event Dynamics [PDF]

arXiv, 2021
Learning the dynamics of spatiotemporal events is a fundamental problem. Neural point processes enhance the expressivity of point process models with deep neural networks. However, most existing methods only consider temporal dynamics without spatial modeling. We propose Deep Spatiotemporal Point Process (\ours{}), a deep dynamics model that integrates
arxiv  

A Closer Look at Spatiotemporal Convolutions for Action Recognition

, 2018
In this paper we discuss several forms of spatiotemporal convolutions for video analysis and study their effects on action recognition. Our motivation stems from the observation that 2D CNNs applied to individual frames of the video have remained solid ...
LeCun, Yann, Paluri, Manohar, Ray, Jamie, Torresani, Lorenzo, Tran, Du, Wang, Heng   +5 more
core   +1 more source

Electrospinning Technology, Machine Learning, and Control Approaches: A Review

Advanced Engineering Materials, Volume 27, Issue 7, April 2025.
Electrospinning produces micro‐ and nanoscale fibers, holding great promise in biomedical engineering. Industrial adoption faces challenges in controlling fiber properties, reproducibility, and scalability. This review explores electrospinning techniques, modeling, and machine learning for process optimization.
Arya Shabani, Gorkem Anil Al, Nael Berri, Bernardo Castro‐Dominguez, Hannah S. Leese, Uriel Martinez‐Hernandez   +5 more
wiley   +1 more source

Spatiotemporal assessments of nutrients and water quality in coastal areas using remote sensing and a spatiotemporal deep learning model

International Journal of Applied Earth Observations and Geoinformation, 2022
Revealing the spatiotemporal variations of nutrients in coastal waters is crucial to the understanding and evaluation of coastal environment, thereby providing efficient guidance for the aquatic environmental treatment.
Sensen Wu, Jin Qi, Zhen Yan, Fangzheng Lyu, Tao Lin, Yuanyuan Wang, Zhenhong Du   +6 more
doaj  

Spatiotemporal CNNs for Pornography Detection in Videos

, 2018
With the increasing use of social networks and mobile devices, the number of videos posted on the Internet is growing exponentially. Among the inappropriate contents published on the Internet, pornography is one of the most worrying as it can be accessed
D Moreira, L Maaten van der, M Perez, N Dalal, S Ji   +4 more
core   +1 more source

Biomimetic Design of Biocompatible Neural Probes for Deep Brain Signal Monitoring and Stimulation: Super Static Interface for Immune Response‐Enhanced Contact

Advanced Functional Materials, EarlyView.
Ultrathin, flexible neural probes are developed with an innovative, biomimetic design incorporating brain tissue‐compatible materials. The material system employs biomolecule‐based encapsulation agents to mitigate inflammatory responses, as demonstrated through comprehensive in vitro and in vivo studies.
Jeonghwa Jeong, Gyeonghwa Heo, Young Woo Kwon, Seon Yeong Chae, Min Jae Kim, Ki Jun Yu, Hwa Kyoung Shin, Suck Won Hong   +7 more
wiley   +1 more source

Deep Learning-Based Fishing Ground Prediction Using Asymmetric Spatiotemporal Scales: A Case Study of Ommastrephes bartramii

Fishes
Selecting the optimal spatiotemporal scale in fishing ground prediction models can maximize prediction accuracy. Current research on spatiotemporal scales shows that they are symmetrically distributed, which may not capture specific oceanographic ...
Mingyang Xie, Bin Liu, Xinjun Chen, Wei Yu, Jintao Wang   +4 more
doaj   +1 more source

Traffic Flow Prediction Based on Large Language Models and Future Development Directions [PDF]

ITM Web of Conferences
As the application of deep learning in intelligent transportation systems becomes increasingly widespread, the accuracy and reliability of traffic flow prediction have become crucial.
Zhang Muhua, Zhao Wenzheng
doaj   +1 more source