Results 161 to 170 of about 41,443 (305)

Forecasting Fossil Energy Price Dynamics with Deep Learning: Implications for Global Energy Security and Financial Stability

Algorithms
This study investigates the application of advanced deep learning models to forecast fossil energy prices, a critical factor influencing global economic stability.
Bilal Ahmed Memon
doaj   +1 more source

CMOS‐Integrated Synaptic Photoreceptor Chip Inspired by Insect Visual Processing

Advanced Science, EarlyView.
CMOS‐integrated Si QDs/ReS2 synaptic photoreceptor array mimics the parallel processing and wavelength‐selective strategy of insect vision. By combining intrinsic ultraviolet‐violet sensitivity with synaptic plasticity, the chip enables frontend sensory redundancy reduction without external filters, offering a scalable pathway toward lowpower ...
Jian Chai, Xinyi Xu, Yue Wang, Xiaochen Wang, Hailiang Wang, Yunfei Xie, Xinwei Zhang, Haoyu Wang, Hao Ning, Jiangming Lin, Yongliang Xie, Qihai Jiang, Baoshi Qiao, Xiaolei Ding, Luyao Ma, Shukai Duan, Zhenyi Ni, Huan Hu, Xin He, Fei Xue, Feichi Zhou, Lingfei Li, Srikrishna Chanakya Bodepudi, Rui Yuan, Bin Yu, Yang Xu   +25 more
wiley   +1 more source

Context-aware sentence categorisation: word mover’s distance and character-level convolutional recurrent neural network [PDF]

Supervised k nearest neighbour and unsupervised hierarchical agglomerative clustering algorithm can be enhanced through word mover’s distance-based sentence distance metric to offer superior context-aware sentence categorisation performance.
Fu, Xinyu
core  

Seeing the Wind: Visual Wind Speed Prediction with a Coupled Convolutional and Recurrent Neural Network [PDF]

, 2019
Wind energy resource quantification, air pollution monitoring, and weather forecasting all rely on rapid, accurate measurement of local wind conditions. Visual observations of the effects of wind---the swaying of trees and flapping of flags, for example--
Cardona, Jennifer L., Howland, Michael F., Dabiri, John O.   +2 more
core  

Ultra‐Wide‐Field Noninvasive Imaging Through Scattering Media Via Physics‐Guided Deep Learning

Advanced Science, EarlyView.
We propose a physics‐guided adaptive dual‐domain learning method for ultra‐wide‐field noninvasive imaging through scattering media, namely UNI‐Net. Our method not only reduces the requirement for real experimental data by an order of magnitude but also enables clear imaging of complex scenes with an ultra‐large field of view, which is 164 times the OME
Lintao Peng, Mingwei He, Jeff Zhu, Sujit K. Sahoo, Liheng Bian, Cuong Dang   +5 more
wiley   +1 more source

Engineering Neuronal Network Connectivity Through Precise and Scalable Electrical Modulation

Advanced Science, EarlyView.
This study presents a scalable all‐electrical method for precise neuronal‐circuit reconfiguration based on high‐density microelectrode arrays. By employing biologically inspired plasticity rules, targeted connectivity changes were successfully induced and quantified across diverse neuronal preparations.
Sreedhar S. Kumar, Yannaël Bossard, Rachel Sava, Tobias Gänswein, Lorenca Sadiraj, Jean‐Samuel Dupré, Manuel Schröter, J. Gray Camp, Fernando Cardes, Julian Bartram, Andreas Hierlemann   +10 more
wiley   +1 more source

THE ROLE OF CONVOLUTIONAL NEURAL NETWORK (CNN) AND RECURRENT NEURAL NETWORK (RNN) ON LEADERSHIP AND WORKFORCE AGILITY IN UMSU POSTGRADUATE PROGRAMS

Convolutional Neural Network (CNN) is a development of Multilayer Perceptron (MLP) designed to process and classify data. Recurrent Neural Network (RNN) is an artificial neural network architecture known for its good performance as it processes input ...
ayadi, B. Herawan H, Triwanda, Eri, Wanayumini, Wanayumini   +2 more
core   +1 more source

Blind Interleaver Recognition Using Deep Learning Techniques

IEEE Access
In digital communication systems, channel encoders and interleavers play a crucial role in mitigating the random and burst errors introduced by noisy channels.
Nayim Ahamed, Swaminathan R., B. Naveen
doaj   +1 more source

SpaMode: A Broadly Applicable Framework for Deciphering Spatial Multi‐Omics Using Multimodal Mixture of Disentangled Experts

Advanced Science, EarlyView.
SpaMode introduces a versatile framework for spatial multi‐omics integration across vertical, horizontal, and mosaic scenarios. By disentangling modality‐invariant and variant features through a mixture‐of‐experts mechanism, it adaptively reconfigures spatially heterogeneous signals.
Xubin Zheng, Xinlei Huang, Xiang Zhou, Dian Meng, Ziyue Qiao, Zhiyuan Yuan, Lixin Cheng   +6 more
wiley   +1 more source

Convolutional over Recurrent Encoder for Neural Machine Translation

, 2017
Neural machine translation is a recently proposed approach which has shown competitive results to traditional MT approaches. Standard neural MT is an end-to-end neural network where the source sentence is encoded by a recurrent neural network (RNN ...
Christof Monz, Praveen Dakwale
core   +1 more source