Learning deep hierarchical and temporal recurrent neural networks with residual learning
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-020-01063-0
Abstract: Learning both hierarchical and temporal dependencies can be crucial for recurrent neural networks (RNNs) to deeply understand sequences. To this end, a unified RNN framework is required that can ease the learning of both the… read more here.
Keywords: learning deep; neural networks; hierarchical temporal; residual learning ... See more keywords
Deep hierarchical embedding for simultaneous modeling of GPCR proteins in a unified metric space
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-88623-8
Abstract: GPCR proteins belong to diverse families of proteins that are defined at multiple hierarchical levels. Inspecting relationships between GPCR proteins on the hierarchical structure is important, since characteristics of the protein can be inferred from… read more here.
Keywords: space; modeling gpcr; hierarchical embedding; gpcr proteins ... See more keywords
Deep Hierarchical Strategy Model for Multi-Source Driven Quantitative Investment
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2923267
Abstract: Using deep learning to maximize the benefits of a series of risks in the securities market was a very interesting and widely concerned problem. From the perspective of multi-source driving, we proposed a feature combination… read more here.
Keywords: multi source; hierarchical strategy; deep hierarchical; model ... See more keywords
Deep Hierarchical Vision Transformer for Hyperspectral and LiDAR Data Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2022.3162964
Abstract: In this study, we develop a novel deep hierarchical vision transformer (DHViT) architecture for hyperspectral and light detection and ranging (LiDAR) data joint classification. Current classification methods have limitations in heterogeneous feature representation and information… read more here.
Keywords: hyperspectral lidar; classification; deep hierarchical; lidar data ... See more keywords
Deep Hierarchical Ensemble Model for Suicide Detection on Imbalanced Social Media Data
Sign Up to like & getrecommendations! Published in 2022 at "Entropy"
DOI: 10.3390/e24040442
Abstract: As a serious worldwide problem, suicide often causes huge and irreversible losses to families and society. Therefore, it is necessary to detect and help individuals with suicidal ideation in time. In recent years, the prosperous… read more here.
Keywords: social media; suicide detection; deep hierarchical; model ... See more keywords
Speech Emotion Recognition Using Deep Learning LSTM for Tamil Language
Sign Up to like & getrecommendations! Published in 2021 at "Pertanika Journal of Science and Technology"
DOI: 10.47836/pjst.29.3.33
Abstract: Deep Neural Networks (DNN) are more than just neural networks with several hidden units that gives better results with classification algorithm in automated voice recognition activities. Then spatial correlation was considered in traditional feedforward neural… read more here.
Keywords: tamil language; neural networks; speech; recognition ... See more keywords