Dilated-Convolutional Recurent Neural Network untuk Klasifikasi Genre Musik by Mochammad Rizqul Fatichin, Alfado Rafly Hermawan, Raynaldi Anggiat Samuel Siahaan, Rarasmaya Indraswari

“…Penelitian ini mengevaluasi penggunaan Dilated-Convolutional Recurrent Neural Network (D-CRNN) dalam mengklasifikasi genre musik. …”
Get full text

Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction by Ariyo Oluwasanmi, Muhammad Umar Aftab, Zhiguang Qin, Muhammad Shahzad Sarfraz, Yang Yu, Hafiz Tayyab Rauf

“…To solve this challenge, this paper presents a traffic forecasting model which combines a graph convolutional network, a gated recurrent unit, and a multi-head attention mechanism to simultaneously capture and incorporate the spatio-temporal dependence and dynamic variation in the topological sequence of traffic data effectively. …”
Get full text

Detection of human activities using multi-layer convolutional neural network by Essam Abdellatef, Rasha M. Al-Makhlasawy, Wafaa A. Shalaby

“…This paper introduces HARCNN, a novel approach leveraging Convolutional Neural Networks (CNNs) to extract hierarchical spatial and temporal features from raw sensor data, enhancing activity recognition performance. …”
Get full text

Enhancing dance education through convolutional neural networks and blended learning by Zhiping Zhang, Wei Wang

“…Moreover, the integration of motion capture technology with convolutional neural networks (CNNs) facilitates a precise analysis of students’ dance movements, offering detailed feedback and recommendations for improvement. …”
Get full text

Convolutional Neural Network-Based Low Light Image Enhancement Method by M.X. Li, C.J. Xu

Get full text

Fault Identification Model Using Convolutional Neural Networks with Transformer Architecture by Yongxin Fan, Yiming Dang, Yangming Guo

“…To address this, the present study proposes a novel hybrid deep learning framework that integrates Convolutional Neural Networks (CNN) for feature extraction with Transformer architecture for temporal modeling. …”
Get full text

Frequency Enhanced Dynamic Graph Convolutional Networks for Traffic Flow Forecasting by Liyuan Wang, Jiafeng Zhuang, Shuo Ma, Hai Lin

“…Recent advancements in deep learning, particularly Graph Convolutional Networks (GCNs), offer more effective solutions for traffic forecasting. …”
Get full text

Dynamic Hypergraph Convolutional Networks for Hand Motion Gesture Sequence Recognition by Dong-Xing Jing, Kui Huang, Shi-Jian Liu, Zheng Zou, Chih-Yu Hsu

“…This paper introduces a novel approach to hand motion gesture recognition by integrating the Fourier transform with hypergraph convolutional networks (HGCNs). Traditional recognition methods often struggle to capture the complex spatiotemporal dynamics of hand gestures. …”
Get full text

Spatiotemporal analysis of mangroves using median composites and convolutional neural network by Kathiroli R, Madhumitha P S, Achyut Prasad D C, Sandhiya S

Get full text

Optimized Attention Enhanced Temporal Graph Convolutional Network Espoused Research of Intelligent Customer Service System based on Natural Language Processing Technology by Zhifeng Wei, Hongyan Wang, Qiang Xu, Yi Qu, Wei Xing

Get full text

PM2.5 prediction and its influencing factors in the Beijing-Tianjin-Hebei urban agglomeration using spatial temporal graph convolutional networks by Yawen Zhao

“…To address this, this study uses spatiotemporal analysis and Spatial Temporal Graph Convolutional Networks (ST-GCN) to evaluate the variation and driving factors of PM _2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) urban agglomeration from 2014 to 2024, and to make predictions. …”
Get full text

A Hybrid Long Short-Term Memory-Graph Convolutional Network Model for Enhanced Stock Return Prediction: Integrating Temporal and Spatial Dependencies by Songze Shi, Fan Li, Wei Li

“…This study proposes a hybrid model integrating long short-term memory (LSTM) networks and graph convolutional networks (GCNs) to enhance accuracy by capturing both temporal dynamics and spatial inter-stock relationships. …”
Get full text

Integrated Spatio-Temporal Graph Neural Network for Traffic Forecasting by Vandana Singh, Sudip Kumar Sahana, Vandana Bhattacharjee

Subjects: “…graph convolutional neural network…”
Get full text

Abnormal gait recognition with millimetre‐wave radar based on perceptual loss and convolutional temporal autoencoder by Peng Zhao, Ling Hong, Yu Wang

“…This paper proposes a novel abnormal gait recognition method based on a perceptual loss convolutional temporal autoencoder (PLCTAE) network. …”
Get full text

Predicting Index Trend Using Hybrid Neural Networks with a Focus on Multi-Scale Temporal Feature Extraction in the Tehran Stock Exchange by Mohammad Osoolian, Ali Nikmaram, Mahdi Karimi

“…MethodsThe hybrid neural network architecture that has been put forward integrates the unique capabilities of convolutional neural networks (CNNs) in the realm of feature extraction with the effectiveness of long short-term memory (LSTM) networks in capturing temporal dependencies. …”
Get full text

Intrusion Detection and Mitigation Method for the Industrial Internet of Things Using Bidirectional Convolutional Long Short-Term Memory and Deep Recurrent Convolutional Q-Networks by Zhang Yan, Piyush Kumar Shukla, Prashant Kumar Shukla, Kanika Thakur, Anurag Sinha, Saifullah Khalid

“…The intrusion detection phase uses a combination of deep convolutional neural networks (DCNN) and bidirectional long short-term memory (BI-LSTM) networks to capture both spatial and temporal relationships in the data, while a hybrid feature selection technique improves the model’s performance. …”
Get full text

Disentangled diffusion dodels for probabilistic spatio-temporal traffic forecasting by Wenyu Zhang, Kaidong Zheng

Subjects: Get full text

Cloud based real-time multivariate multi-step prediction of systolic blood pressure and heart rate using temporal convolutional network and Apache Spark by Hager Saleh, Nora El-Rashidy, Sherif Mostafa, Abdulaziz AlMohimeed, Shaker El-Sappagh, Zainab H. Ali

Subjects: Get full text

Pedestrian Trajectory Prediction Based on Transformer and Multi-relation Graph Convolutional Networks by LIU Guihong, ZHOU Zongrun, MENG Xiangfu

“…Pedestrian trajectories are highly random, dynamic, and influenced by their surroundings, necessitating the effective modeling of their temporal and spatial interactions. To address this, a pedestrian trajectory prediction model combining Transformer and multi-relation graph convolutional network (GCN) is proposed. …”
Get full text

Ultrawideband Non-Line-of-Sight Classification Using Transformer-Convolutional Neural Networks by Hae-Ji Hwang, Seon-Geun Jeong, Won-Joo Hwang

“…The Transformer captures global temporal dependencies through self-attention, while convolutional neural networks efficiently extract local spatial features. …”
Get full text