Multimodal information fusion based on LSTM for 3D model retrieval
Sign Up to like & getrecommendations! Published in 2020 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-08817-6
Abstract: With advances in low-cost 3D model capturing devices and virtual 3D model building software, the acquisition of 3D data has become increasingly easier. The subsequent 3D model retrieval skill has also become essential when we… read more here.
Keywords: model retrieval; information; based lstm; model ... See more keywords
A New Regularized Spatiotemporal Attention-Based LSTM with Application to Nitrogen Oxides Emission Prediction
Sign Up to like & getrecommendations! Published in 2023 at "ACS Omega"
DOI: 10.1021/acsomega.2c08205
Abstract: The data collected from complex process industries are usually time series with considerable nonlinearities and dynamics, as well as excessive redundancy. Moreover, there are temporal and spatial correlations between input variables and key performance variables.… read more here.
Keywords: spatiotemporal attention; new regularized; attention based; regularized spatiotemporal ... See more keywords
Neurological state changes indicative of ADHD in children learned via EEG-based LSTM networks
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/ac4f07
Abstract: Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that pervasively interferes with the lives of individuals starting in childhood. Objective. To address the subjectivity of current diagnostic approaches, many studies have been dedicated to efforts to… read more here.
Keywords: state; adhd children; based lstm; lstm networks ... See more keywords
PV Power Prediction Based on LSTM With Adaptive Hyperparameter Adjustment
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2936597
Abstract: The randomness, volatility, and intermittence of solar power generation make it difficult to achieve the desired accuracy of PV output-power prediction. Therefore, the time learning weight (TLW) proposed in this paper is used to improve… read more here.
Keywords: based lstm; power; prediction; power prediction ... See more keywords
Identifying and Classifying Enhancers by Dinucleotide-Based Auto-Cross Covariance and Attention-Based Bi-LSTM
Sign Up to like & getrecommendations! Published in 2022 at "Computational and Mathematical Methods in Medicine"
DOI: 10.1155/2022/7518779
Abstract: Enhancers are a class of noncoding DNA elements located near structural genes. In recent years, their identification and classification have been the focus of research in the field of bioinformatics. However, due to their high… read more here.
Keywords: cross covariance; based lstm; auto cross; attention based ... See more keywords