An Approach for Detecting Tomato Under a Complicated Environment by Chen-Feng Long, Yu-Juan Yang, Hong-Mei Liu, Feng Su, Yang-Jun Deng

“…Tomato is one of the most popular and widely cultivated fruits and vegetables in the world. …”
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A Multi-Task Spatiotemporal Graph Neural Network for Transient Stability and State Prediction in Power Systems by Shuaibo Wang, Xinyuan Xiang, Jie Zhang, Zhuohang Liang, Shufang Li, Peilin Zhong, Jie Zeng, Chenguang Wang

“…To address these challenges, this paper presents a multi-task learning framework based on spatiotemporal graph convolutional networks that efficiently performs both tasks. …”
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GNSS–VTEC prediction based on CNN–GRU neural network model during high solar activities by T. Y. Yang, J. Y. Lu, Y. Y. Yang, Y. H. Hao, M. Wang, J. Y. Li, G. C. Wei

“…In this study, a model combining Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) network has been constructed to forecast the TEC during high solar activities from a single Global Navigation Satellite System (GNSS) receiver at Sanya in Hainan, China. …”
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Dynamic graph attention network based on multi-scale frequency domain features for motion imagery decoding in hemiplegic patients by Yinan Wang, Yinan Wang, Lizhou Gong, Yang Zhao, Yewei Yu, Hanxu Liu, Xiao Yang

“…MFF-DANet employs convolutional kernels of various scales to extract feature information across multiple frequency bands, followed by a channel attention-based average pooling operation to retain the most critical frequency domain features. …”
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Time–frequency ensemble network for wind turbine mechanical fault diagnosis by Haiyu Guo, Xingzheng Guo, Xiaoguang Zhang, Fanfan Lu, Chuang Liang

“…Second, the Transformer and Graph Convolutional Network (GCN) are combined to extract the time–frequency discriminative features of defects. …”
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Detection and classification of hypertensive retinopathy based on retinal image analysis using a deep learning approach by Bambang Krismono Triwijoyo, Ahmat Adil, Muhammad Zulfikri

“…Background: The issue is that most heart attacks and strokes happen unexpectedly to people who have signs of high blood pressure that are not identified in time for treatment. …”
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Ulcerative Severity Estimation Based on Advanced CNN–Transformer Hybrid Models by Boying Nie, Gaofeng Zhang

“…This study aims to apply a state-of-the-art hybrid neural network architecture—combining convolutional neural networks (CNNs) and transformer models—to classify intestinal endoscopy images, utilizing the largest publicly available annotated UC dataset. …”
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Enhancing Situational Awareness: Anomaly Detection Using Real-Time Video Across Multiple Domains by Rajan Singh, Amrit Pal, Shruti Mishra, Abishi Chowdhury

“…This paper proposes a novel approach to handle the complexity of dynamic real-world anomaly detection scenarios using three state of the art machine learning models: Convolutional Neural Networks (CNN), Region-based Convolutional Neural Network (R-CNN), and You Only Look Once (YOLO). …”
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A Comparative Study of Data-Driven Prognostic Approaches under Training Data Deficiency by Jinwoo Song, Seong Hee Cho, Seokgoo Kim, Jongwhoa Na, Joo-Ho Choi

“…While the data-driven approach is the most common for this purpose, they often face challenges due to insufficient training data. …”
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Classification of Structural and Functional Development Stage of Cardiomyocytes Using Machine Learning Techniques by V. R. Bondarev, K. O. Ivanko, N. G. Ivanushkina

“…Cell regenerative therapy has become one of the most promising treatment options for patients with heart failure. …”
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Joint fusion of sequences and structures of drugs and targets for identifying targets based on intra and inter cross-attention mechanisms by Xin Zeng, Guang-Peng Su, Wen-Feng Du, Bei Jiang, Yi Li, Zi-Zhong Yang

“…MM-IDTarget integrates some cutting-edge deep learning techniques such as graph transformer, multi-scale convolutional neural networks (MCNN), and residual edge-weighted graph convolutional network (EW-GCN) to extract sequence and structure modal features of drugs and targets. …”
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A Novel Traffic Flow Forecasting Method Based on RNN-GCN and BRB by Hailong Zhu, Yawen Xie, Wei He, Chao Sun, Kaili Zhu, Guohui Zhou, Ning Ma

“…Traffic flow forecasting provides a reliable traffic dispatch basis for intelligent transport, and most of the existing prediction methods only predict a single saturation or speed and do not use the saturation and speed in a unified way. …”
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Safeguarding the Integrity of Online Social Networks (OSN): Leveraging the Efficacy of Conv-LSTM-Based Siamese Network to Predict Hate Speech in Low Resource Hindi-English Code-Mix... by Shankar Biradar, Sunil Saumya, Sanjana Kavatagi

“…We propose a Convolution-LSTM network that incorporates spatial and temporal features. …”
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Research on machine learning methods for detecting objects in difficult shooting conditions by Vitalii Serdechnyi, Olesia Barkovska, Andriy Kovalenko, Anton Havrashenko, Vitalii Martovytskyi

“…The goal of this research is to identify the most effective deep learning models based on convolutional neural networks for object detection tasks under challenging imaging conditions, considering the practical requirements for accuracy and processing speed. …”
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Backdoor Defence for Voice Print Recognition Model Based on Speech Enhancement and Weight Pruning by Jiawei Zhu, Lin Chen, Dongwei Xu, Wenhong Zhao

“…Voice print recognition is one of the most mature biometric authentication technologies, and the application of deep neural networks (DNNs) has led to a significant improvement in the accuracy of voice print recognition. …”
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Enhancing anemia detection through multimodal data fusion: a non-invasive approach using EHRs and conjunctiva images by Muhammad Ramzan, Muhammad Usman Saeed, Ghulam Ali

“…First, EHR records are preporcessed by selecting the most appropriate features using Random Forest. The features from the conjunctiva images are extracted using RCBAM (Reverse Convolution Block Attention Mechanism). …”
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Deep Learning–Based Prediction of Freezing of Gait in Parkinson's Disease With the Ensemble Channel Selection Approach by Sara Abbasi, Khosro Rezaee

“…This architecture, adaptable to a convolution bottleneck attention–BiLSTM (CBA‐BiLSTM), classifies signals using data from ankle, leg, and trunk sensors. …”
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An Effective Hybrid Deep Neural Network for Arabic Fake News Detection by Tahseen A. Wotaifi, Ban N. Dhannoon

“… Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. …”
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Unbalanced Feature Identification of Rotor System Based on Fused Cross-Correlation Fast Fourier Transform by Yiheng Sheng, Zinan Wang, Peng Zhou, Zhan Wang, Qian Wang, Siqi Niu

“…Rotor system unbalance is one of the most important factors that affects the operating accuracy and stability in aerospace engineering. …”
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Segmented Frequency-Domain Correlation Prediction Model for Long-Term Time Series Forecasting Using Transformer by Haozhuo Tong, Lingyun Kong, Jie Liu, Shiyan Gao, Yilu Xu, Yuezhe Chen

“…Furthermore, we introduce an isometry convolution method to enhance the prediction accuracy of the model. …”
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