资讯

IEEE1月

Convolutional Spatio-Temporal Prediction Network with Trainable Positional Encoding

Abstract: Existing spatio-temporal prediction networks that rely on recurrent neural networks face significant parallelization challenges, leading to high computational costs and prolonged training ...
C&EN5月

Interpretable Multiscale Convolutional Neural Network for Classification and Feature ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Raman spectroscopy in biological applications faces challenges due to complex spectra, ...
pv magazine International5月

Ultra-short-term PV forecasting based on convolutional neural network, long short-term memory

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...
C&EN7月

Convolutional Neural Networks Assisted Peak Classification in Targeted LC-HRMS/MS for ...

GIE LCH, Laboratoire des Courses Hippiques, 15 rue de Paradis, 91370 Verrières-le-Buisson, France ...
Frontiers4 年

A Monte Carlo Simulation Approach in Non-linear Structural Dynamics Using Convolutional ...

The evaluation of the structural response statistics constitutes one of the principal tasks in engineering. However, in the tail region near structural failure, engineering structures behave highly ...
IEEE4 年

Trainable Spectrally Initializable Matrix Transformations in Convolutional Neural Networks

Abstract: In this work, we introduce a new architectural component to Neural Network (NN), i.e., trainable and spectrally initializable matrix transformations on feature maps. While previous ...
Frontiers6 年

Dual Convolutional Neural Networks With Attention Mechanisms Based Method for Predicting ...

A lot of studies indicated that aberrant expression of long non-coding RNA genes (lncRNAs) is closely related to human diseases. Identifying disease-related lncRNAs (disease lncRNAs) is critical for ...