Automatic Number Plate Detection and Recognition System for Small-Sized Number Plates of Category L-Vehicles for Remote Emission Sensing Applications by Hafiz Hashim Imtiaz, Paul Schaffer, Paul Hesse, Martin Kupper, Alexander Bergmann

Get full text

An Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model by Rajesh Kannan Megalingam, Kariparambil Sudheesh Sankardas, Sakthiprasad Kuttankulangara Manoharan

Get full text

Neuroevolutionary reinforcing learning of neural networks by Y. A. Bury, D. I. Samal

Get full text

Artificial intelligence in acoustic ecology: Soundscape classification in the Cerrado by Bruno Daleffi da Silva, Linilson Rodrigues Padovese

“…The conclusion is that it is possible to classify different Cerrado formations through their acoustic landscape, and the choice of the optimal model for classification should consider a balance between accuracy, operational complexity, and efficiency. …”
Get full text

Origin-destination prediction from road average speed data using GraphResLSTM model by Guangtong Hu, Jun Zhang

“…This article presents a novel integrated framework, effectively merging the distinctive capabilities of graph convolutional network (GCN), residual neural network (ResNet), and long short-term memory network (LSTM), hereby designated as GraphResLSTM. …”
Get full text

Development of weighted residual RNN model with hybrid heuristic algorithm for movement recognition framework in ambient assisted living by Mustufa Haider Abidi, Hisham Alkhalefah, Zeyad Almutairi

“…Subsequently, the essential deep features are extracted from the input data using a Convolutional Autoencoder. Finally, the resultant features are subjected to the movement recognition model, termed as Weighted Residual Recurrent Neural Network. …”
Get full text

UniLF: A novel short-term load forecasting model uniformly considering various features from multivariate load data by Shiyang Zhou, Qingyong Zhang, Peng Xiao, Bingrong Xu, Geshuai Luo

“…Experiments conducted on three load datasets from Australia, Panama and Austria show that UniLF achieves superior forecasting accuracy with competitive practical efficiency under different prediction lengths, providing a new solution for STLF.…”
Get full text

Research on the Application of Deep Learning Algorithm in the Damage Detection of Steel Structures by Qingyun Ge, Caimei Li, Fulian Yang

“…This study introduces a novel Convolutional Long Short-Term Memory (ConvLSTM) network for steel structure damage detection, aimed at enhancing the accuracy and reliability of structural health monitoring systems. …”
Get full text

Enhanced Emotion-Aware Conversational Agent: Analyzing User Behavioral Status for Tailored Reponses in Chatbot Interactions by S. Abinaya, K. S. Ashwin, A. Sherly Alphonse

“…This processed image is analyzed by a Convolutional Neural Network (CNN) model trained specifically for emotion recognition, reaching 74.14% accuracy by assigning probabilities to different emotions. …”
Get full text

CLSTM-MT (a Combination of 2-Conv CNN and BiLSTM Under the Mean Teacher Collaborative Learning Framework): Encryption Traffic Classification Based on CLSTM (a Combination of 2-Conv... by Xiaozong Qiu, Guohua Yan, Lihua Yin

Get full text

Enhancing advanced cervical cell categorization with cluster-based intelligent systems by a novel integrated CNN approach with skip mechanisms and GAN-based augmentation by Gunjan Shandilya, Sheifali Gupta, Ahmad Almogren, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Seada Hussen

“…Here, a customized Convolutional Neural Network (CNN) model is proposed for cervical cancerous cell detection. …”
Get full text

A spatio-temporal fusion-based approach for multi-dimensional classification of Parkinson’s disease progression using multi-modal dataset by Vinay Kukreja, Vandana Ahuja, Modafar Ati, Hariharan Shanmugasundaram, Murugaperumal Krishnamoorthy, Rishabh Sharma, Abhishek Bhattacherjee

“…Context: The progressive neurodegenerative disorder Parkinson’s disease (PD) features diverse symptom presentation that progresses at different speeds and demands effective disease classification with precise patient management. …”
Get full text

A practical temporal transfer learning model for multi-step water quality index forecasting using A CNN-coupled dual-path LSTM network by Kok Poh Wai, Chai Hoon Koo, Yuk Feng Huang, Woon Chan Chong, Ahmed El-Shafie, Mohsen Sherif, Ali Najah Ahmed

“…A hybrid deep learning architecture was developed by combining a 1d-Convolutional Neural Network (CNN) with a dual-path Long Short-Term Memory (LSTM) network to capture long-term hydrological memory and site-specific temporal variability. …”
Get full text

Hybrid Multi-Branch Attention–CNN–BiLSTM Forecast Model for Reservoir Capacities of Pumped Storage Hydropower Plant by Yu Gong, Hao Wu, Junhuang Zhou, Yongjun Zhang, Langwen Zhang

“…In order to better distinguish the effects of different data types on the reservoir capacity, the correlation between data and reservoir capacity is analyzed using the Spearman coefficient, and a multi-branch forecast model is established based on the correlation. …”
Get full text

HDTFF-Net: Hierarchical Deep Texture Features Fusion Network for High-Resolution Remote Sensing Scene Classification by Wanying Song, Yifan Cong, Shiru Zhang, Yan Wu, Peng Zhang

“…Fusing features from different feature descriptors or different convolutional layers can improve the understanding of scene and enhance the classification accuracy. …”
Get full text

Boosting Arabic text classification using hybrid deep learning approach by Eman Alnagi, Rawan Ghnemat, Qasem Abu Al-Haija

“…Deep Learning architectures, such as convolutional neural networks (CNN) and long short-term memory (LSTM), have been widely utilized to categorize and organize language contents accurately to improve the autonomy and perception of NLP tasks. …”
Get full text

From Binary to Multi-Class: Neural Networks for Structural Damage Classification in Bridge Monitoring Under Static and Dynamic Loading by Andreas Kardoulias, Alexandros Arailopoulos, Panagiotis Seventekidis

Get full text

Ultra Short-Term Charging Load Forecasting Based on Improved Data Decomposition and Hybrid Neural Network by Shaoyang Yin, Zhaohui Chen, Wanyuan Liu, Zhiwen Su

“…To address the problem of the strong nonlinearity of power load sequences, this study proposes an ultra-short-term charging load prediction model that combines a Time Convolutional Network-Bidirectional Gated Recurrent Unit (TCN-Bi-GRU)and uses the Osprey Optimization Algorithm (OOA) based on the opposition-based learning strategy to optimize Variational Mode Decomposition (VMD). …”
Get full text

Studying the influence of correction codes on coherent reception of M-PSK signals in the presence of noise and harmonic interference by V. D. Nguyen

“…One of the important requirements for the quality of data transmission is the system error tolerance. There are different ways of improving the quality of information transmission. …”
Get full text

StaEn-IDS: An Explainable Stacking Ensemble Deep Neural Network-Based Intrusion Detection System for IoT by Monika Vishwakarma, Nishtha Kesswani

“…With millions of connected devices from different manufacturers using various protocols and IoT applications, ensuring IoT security is challenging. …”
Get full text