3D convolution network and Siamese-attention mechanism for expression recognition
Sign Up to like & getrecommendations! Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-07860-2
Abstract: Researches on Expression recognition focus on common subject-independent task, while cross-database evaluation is rare and lack of universal protocol. The key challenge for both tasks is to extract features that effectively describe the pattern of… read more here.
Keywords: convolution network; expression recognition; network; attention mechanism ... See more keywords
End-to-end dilated convolution network for document image semantic segmentation
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Central South University"
DOI: 10.1007/s11771-021-4731-9
Abstract: Semantic segmentation is a crucial step for document understanding. In this paper, an NVIDIA Jetson Nano-based platform is applied for implementing semantic segmentation for teaching artificial intelligence concepts and programming. To extract semantic structures from… read more here.
Keywords: network; end; dilated convolution; segmentation ... See more keywords
Lite AU convolution network driven by a small amount of samples
Sign Up to like & getrecommendations! Published in 2017 at "Electronics Letters"
DOI: 10.1049/el.2017.0272
Abstract: A novel lite action unit (AU) convolution network (LAUCN) is proposed for automatic AU detection, which could improve the accuracy of AU detection with a few samples. (i) LAUCN could transform the manual intervened factors… read more here.
Keywords: convolution network; small amount; amount samples;
Spatial-Temporal Aggregation Graph Convolution Network for Efficient Mobile Cellular Traffic Prediction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2021.3138075
Abstract: Accurate cellular traffic prediction is challenging due to the complex spatial topology of cellular network and the dynamic temporal feature of mobile traffic. To overcome these problems, this letter proposes a spatial-temporal aggregation graph convolution… read more here.
Keywords: spatial temporal; traffic; convolution network; graph convolution ... See more keywords
An Optimized Temporal-Spatial Gated Graph Convolution Network for Traffic Forecasting
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Intelligent Transportation Systems Magazine"
DOI: 10.1109/mits.2019.2962138
Abstract: Traffic forecasting is a challenging problem because of the irregular and complex road network in space and the dynamic and non-stationary traffic flow in time. To solve this problem, the recently proposed temporal graph convolution… read more here.
Keywords: traffic; convolution network; graph convolution; network ... See more keywords
Continuous Volumetric Convolution Network With Self-Learning Kernels for Point Clouds
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Consumer Electronics"
DOI: 10.1109/tce.2022.3218107
Abstract: Although Convolutional Neural Networks (CNNs) have achieved large successes on image data, the attributes of point cloud data, such as its irregular format and sparse 3D distribution, prevent CNNs from being applied to point cloud… read more here.
Keywords: point clouds; self learning; convolution network; continuous volumetric ... See more keywords
Dual Dynamic Spatial-Temporal Graph Convolution Network for Traffic Prediction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2022.3208943
Abstract: Recently, Graph Convolution Network (GCN) and Temporal Convolution Network (TCN) are introduced into traffic prediction and achieve state-of-the-art performance due to their good ability for modeling the spatial and temporal property of traffic data. In… read more here.
Keywords: traffic prediction; convolution network; traffic; graph ... See more keywords
Stock price forecasting based on improved time convolution network
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence"
DOI: 10.1111/coin.12519
Abstract: Stock forecasting is difficult because of its complexity and uncertainty. To better predict stock prices and then provide stockholders with reasonable suggestions, this paper proposes an improved time convolution network (TCN) model for predicting stock… read more here.
Keywords: network; convolution network; improved time; time convolution ... See more keywords
Alzheimer's Disease Analysis Algorithm Based on No-threshold Recurrence Plot Convolution Network
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Aging Neuroscience"
DOI: 10.3389/fnagi.2022.888577
Abstract: Alzheimer's disease is a neurological disorder characterized by progressive cognitive dysfunction and behavioral impairment that occurs in old. Early diagnosis and treatment of Alzheimer's disease is great significance. Electroencephalography (EEG) signals can be used to… read more here.
Keywords: plot convolution; disease; alzheimer disease; convolution network ... See more keywords
Temporal Convolution Network Based Joint Optimization of Acoustic-to-Articulatory Inversion
Sign Up to like & getrecommendations! Published in 2021 at "Applied Sciences"
DOI: 10.3390/app11199056
Abstract: Articulatory features are proved to be efficient in the area of speech recognition and speech synthesis. However, acquiring articulatory features has always been a difficult research hotspot. A lightweight and accurate articulatory model is of… read more here.
Keywords: inversion; temporal convolution; model; articulatory ... See more keywords