Results 51 to 60 of about 84,629 (319)

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

Deep learning predicts microbial interactions from self-organized spatiotemporal patterns

Computational and Structural Biotechnology Journal, 2020
Microbial communities organize into spatial patterns that are largely governed by interspecies interactions. This phenomenon is an important metric for understanding community functional dynamics, yet the use of spatial patterns for predicting microbial interactions is currently lacking.
Joon-Yong Lee, Natalie C. Sadler, Robert G. Egbert, Christopher R. Anderton, Kirsten S. Hofmockel, Janet K. Jansson, Hyun-Seob Song   +6 more
openaire   +3 more sources

Learning to Extract Motion from Videos in Convolutional Neural Networks

, 2016
This paper shows how to extract dense optical flow from videos with a convolutional neural network (CNN). The proposed model constitutes a potential building block for deeper architectures to allow using motion without resorting to an external algorithm,
BKP Horn, D Fleet, D Fortun, DJ Butler, DJ Heeger, EH Adelson, F Solari, GW Taylor, KG Derpanis, KG Derpanis, NC Rust, T Brox, T Brox, V Ulman, YA LeCun   +14 more
core   +1 more source

Electroactive Metal–Organic Frameworks for Electrocatalysis

Advanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska, Yutong Luo, Ruyan Zhao, Jianjun Zhang, Mingchao Wang, Xinliang Feng, Eike Brunner, Stefan Kaskel   +7 more
wiley   +1 more source

Action Recognition Based on Two-Stream Convolutional Networks With Long-Short-Term Spatiotemporal Features

IEEE Access, 2020
Human action recognition is an important research topic in the field of computer vision due to its application values. Recently, a variety of approaches based on deep learning features have been proposed due to the effectiveness of deep neural networks ...
Yanqin Wan, Zujun Yu, Yao Wang, Xingxin Li   +3 more
doaj   +1 more source

Spatiotemporal Deep Learning Network for High-Latitude Ionospheric Phase Scintillation Forecasting

Navigation, 2023
In this paper, we present a spatiotemporal deep learning (STDL) network to conduct binary phase scintillation forecasting at a high-latitude global navigation satellite systems (GNSS) station.
Yunxiang Liu, Zhe Yang, Y. Jade Morton, Ruoyu Li   +3 more
doaj   +1 more source

Naturally Derived Donor‐π‐Acceptor Compounds for Efficient Long‐Wavelength LEDs/Sunlight‐Induced Polymerization and High‐Precision Multiple 3D Printing

Advanced Functional Materials, EarlyView.
Two novel donor–π–acceptor photoinitiators enable ultrafast long‐wavelength photopolymerization under blue/green LEDs and sunlight. Effective at low intensities and concentrations, they overcome slow kinetics and permit rapid 3D printing via DLW, DLP, and LCD methods.
Ji Feng, Tong Gao, Fabrice Morlet‐Savary, Michael Schmitt, Céline Dietlin, Jing Zhang, Pu Xiao, Frédéric Dumur, Jean‐Patrick Joly, Jacques Lalevée   +9 more
wiley   +1 more source

Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network [PDF]

, 2021
Maryam Doborjeh, Zohreh Doborjeh, Nikola Kasabov, Molood Barati, Grace Wang   +4 more
openalex   +1 more source

Universal Neuromorphic Element: NbOx Memristor with Co‐Existing Volatile, Non‐Volatile, and Threshold Switching

Advanced Functional Materials, EarlyView.
A W/NbOx/Pt memristor demonstrates the coexistence of volatile, non‐volatile, and threshold switching characteristics. Volatile switching serves as a reservoir computing layer, providing dynamic short‐term processing. Non‐volatile switching, stabilized through ISPVA, improves reliable long‐term readout. Threshold switching operates as a leaky integrate
Ungbin Byun, Hyesung Na, Sungjun Kim
wiley   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source