Sulfur-Fumigated Ginger Identification Method Based on Meta-Learning for Different Devices by Tianshu Wang, Jiawang He, Hui Yan, Kongfa Hu, Xichen Yang, Xia Zhang, Jinao Duan

“…Although sulfur fumigation methods can effectively prevent ginger from becoming moldy, they cause residual sulfur dioxide, harming human health. …”
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A Secure Communication Method for Unmanned Undersea Systems Oriented to Federated Learning by Jiajia WU, Ming XU

“…To address the information leakage issue in unmanned undersea systems, a secure communication method oriented to federated learning was proposed in this paper. …”
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Noise Currents Measurement Method for Rail Vehicles Based on Broad Learning System by HAN Ran, LI Jie, LIAN Cheng, ZHANG Kun

“…In order to improve test efficiency and reduce costs, this paper proposes a vehicle noise current measurement method based on the broad learning system (BLS). Firstly, the current data samples obtained by flexible current loop and data recorder are divided, and then Fourier transform (FFT) is performed on the divided samples. …”
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Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network by Asroni Asroni, Ku Ruhana Ku-Mahamud, Cahya Damarjati, Hasan Basri Slamat

“…To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to evaluate the pronunciation of the Arabic alphabet. …”
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Vocal performance evaluation of the intelligent note recognition method based on deep learning by Dongyun Chang

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Feasibility of the Anchor-Free Deep Learning Method in Coronary Stenosis Automatic Detection by Hanlin Yue, Wei Yu, Ji Dong, Yunfei Lai, You Wu, Haixia Zhao, Yiwei Song, Li Zhao, Hui Wang, Jing Zhang, Xinping Xu, Binwei Yao, Jianghao Zhao, Kexian Wang, Yue Sun, Haoyu Wang, Ruiyun Peng

“…The main purpose of this paper was to investigate the feasibility of an anchor-free deep learning (DL) method, fully convolutional one-stage object detection (FCOS), in coronary artery stenosis automatic detection. …”
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A Deep Learning-Based Method for Object Workpiece Recognition and Grasp Detection by Yunhan Li, Jingjing Lou, Zhiduan Cai, Chuan Ye, Ruichao Zhao, Yuhang Jiang

“…Experimental results demonstrate that the proposed method effectively handles the interference caused by uneven lighting, achieving a recognition accuracy of 92.2% and an overall average grasping success rate of 93.75%, confirming the feasibility and effectiveness of the approach.…”
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Adversarial Hierarchical-Aware Edge Attention Learning Method for Network Intrusion Detection by Hao Yan, Jianming Li, Lei Du, Binxing Fang, Yan Jia, Zhaoquan Gu

“…To handle these problems, we propose a novel graph neural network–based method for network intrusion detection called the adversarial hierarchical-aware edge attention learning method (AH-EAT). …”
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Fault Location Method for Communication Link in Smart Substation Based on Deep Learning by Zhiyong PI, Yi ZHU, Xuan LIAO, Zhenxing LI, Hao FANG, Pei WU

“…Aiming at the problem of low troubleshooting efficiency of communication link faults caused by complex links in smart substation, a deep learning based fault location method for intelligent substation communication link of smart substation is proposed. …”
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A Method of Smoke Area Segmentation for Infrared Images Based on Deep Learning by QI Hang, YUAN Jianquan, LI Lei, REN Jun, LIANG Jie

“…In this paper, we proposed a smoke area segmentation method for infrared images based on deep learning. …”
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GGSYOLOv5: Flame recognition method in complex scenes based on deep learning. by Fucai Sun, Liping Du, Yantao Dai

“…In this paper, a deep learning-based flame recognition method for complex scenes, GGSYOLOv5, is proposed. …”
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Fault Diagnosis of Rolling Bearing Based on Modified Deep Metric Learning Method by Zengbing Xu, Xiaojuan Li, Hui Lin, Zhigang Wang, Tao Peng

“…A novel fault diagnosis method of rolling bearing based on deep metric learning and Yu norm is proposed in this paper, which is called a deep metric learning method based on Yu norm (DMN-Yu). …”
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A facial structure sampling contrastive learning method for sketch facial synthesis by Kangning Du, Jiyu Zhang, Lin Cao, Yanan Guo, Wenwen Sun

“…To address the above challenges, we propose A Facial Structure Sampling Contrastive Learning Method for Sketch Facial Synthesis. Firstly, we propose a region-constrained sampling module that utilizes the distribution map of facial structure obtained by a dual-branch attention mechanism to segment the input photos into diverse regions, thereby providing regional constraints for sample selection. …”
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A Spatially Informed Machine Learning Method for Predicting Sound Field Uncertainty by Xiangmei Chen, Chao Li, Haibin Wang, Yupeng Tai, Jun Wang, Cyrille Migniot

“…Current machine learning methods excel at improving computational efficiency but face limitations in predictive performance, especially in shadow areas. …”
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A machine learning-based method for predicting the shear behaviors of rock joints by Liu He, Yu Tan, Timothy Copeland, Jiannan Chen, Qiang Tang

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Structural health monitoring and evaluation method for an immersed tunnel based on deep learning by Yuhang Wei, Jinfang Hou, Linhu Yang, Bin Li, Zonghao Ma, Zhao Liu, Wenhao Sun, Binlei Wang

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An Investigation of the Flipped Learning Method to Physical Education Classes in the University: Systematic Review by Procopio B. Dafun Jr., Nurhasan Nurhasan, Heryanto Nur Muhammad, Dyah Fitria Padmasari, Novadri Ayubi

“…This systematic review study reports that the FL method combined with other new techniques in teaching sports in universities provides good results. …”
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Substructure correlation adaptation transfer learning method based on K-means clustering by Haoshuang LIU, Yong ZHANG, Yingbo CAO

“…Domain drifts severely affect the performance of traditional machine learning methods, and existing domain adaptive methods are mainly represented by adaptive adjustment cross-domain through global, class-level, or sample-level distribution adaptation.However, too coarse global matching and class-level matching can lead to insufficient adaptation, and sample-level adaptation to noise can lead to excessive adaptation.A substructure correlation adaptation (SCOAD) transfer learning algorithm based on K-means clustering was proposed.Firstly, multiple subdomains of the source domain and the target domain were obtained by K-means clustering.Then, the matching of the second-order statistics of the subdomain center was sought.Finally, the target domain samples were classified by using the subdomain structure.The proposed method approach further improves the performance of knowledge transfer between the source and target domains on top of the traditional approach.Experimental results on common transfer learning datasets show the effectiveness of the proposed method.…”
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Traffic prediction method based on domain adaptive transfer learning in urban scenarios by XIA Zhenchang, BAN Yijie, TIAN Youliang, LIU Bingyi, CUI Jianqun, CHANG Yanan

“…To address the issues of cross-city transfer capability of traffic prediction models in scenarios with limited data and computing resources, a domain adaptation transfer learning-based traffic prediction method was proposed, along with a transfer learning model and a lightweight spatiotemporal sequence prediction network. …”
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Improving Students' Physics Learning Outcomes Through Implementation of Peer Teaching Method by Yeni Nuriyani, Widodo Winarso

“…Classroom action research using peer teaching methods to improve learning outcomes in physics subject circular motion. …”
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