Rock blasting evaluation - image recognition method based on deep learning by Haibao YI, Aixiang Wu, Xiliang Zhang

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TDQE：a quality evaluation method for text data in deep learning by LUO Chunxu, XIONG Haixu, YE Yazhen, DING Yan, ZONG Shize, XIONG Yun, ZHU Yangyong

“…To address the issues of high computational costs and incomplete evaluation metrics in existing text data quality assessment methods, a deep learning-oriented text data quality evaluation (TDQE) method was proposed. …”
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Deep Reinforcement Learning-Based Deployment Method for Emergency Communication Network by Bo Huang, Yiwei Lu, Hao Ma, Changsheng Yin, Ruopeng Yang, Yongqi Shi, Yu Tao, Yongqi Wen, Yihao Zhong

“…This design effectively mitigates the “curse of dimensionality” inherent in traditional reinforcement learning methods for topology planning. Experimental results demonstrate that the proposed method effectively accomplishes the planning tasks of emergency communication hub elements, significantly improving deployment efficiency while maintaining robustness in complex environments.…”
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DLTM: a deep learning method for tearing mode simulation and prediction by Zhipeng Chang, Baofeng Gao, Ruijie Yin, Xiaofei Zhao

“…In this study, we developed a toolbox called Deep Learning for Tearing Mode, which incorporates two machine learning methods, Tearing-Mode Neural Network and Tearing-Mode Operator Neural Network, to simulate the distributions of perturbation in the linear phase of tearing modes and predict linear growth rates and nonlinear saturated kinetic energy. …”
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Research on deep reinforcement learning based intelligent shop scheduling method by Zihui LUO, Chengling JIANG, Liang LIU, Xiaolong ZHENG, Huadong MA

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A Driver’s Calling Behavior Detection Method Based on Deep Learning by XIONG Qunfang, LIN Jun, YUE Wei, LIU Shiwang, LUO Xiao, DING Chi

“…At present, driver’s calling behavior detection methods are prone to object occlusion, image rotation, illumination change and are difficult to extract deep features of the image, which degrade the detection accuracy. …”
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Lightweight deep learning method for end-to-end point cloud registration by Linjun Jiang, Yue Liu, Zhiyuan Dong, Yinghao Li, Yusong Lin

“…In contrast, deep learning-based registration methods have demonstrated improved accuracy and generalization. …”
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Constructing segmentation method for wheat powdery mildew using deep learning by Hecang Zang, Hecang Zang, Congsheng Wang, Qing Zhao, Qing Zhao, Jie Zhang, Jie Zhang, Junmei Wang, Guoqing Zheng, Guoqing Zheng, Guoqiang Li, Guoqiang Li

“…Compared with other mainstream deep learning methods U-Net, PSPNet, DeepLabV3+, and Swin-Unet, the proposed RSE Swin-Unet method can detect wheat powdery mildew and stripe rust image in a challenging situation and has good computer vision processing and performance evaluation effects. …”
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Transmission Lines Insulator State Detection Method Based on Deep Learning by Xu Tan, Shiying Hou, Fan Yang, Zhimin Li

“…Therefore, to achieve automation in insulator state detection, this paper proposes a method based on deep learning for insulator state detection in transmission lines. …”
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Benchmark dataset and deep learning method for global tropical cyclone forecasting by Cheng Huang, Pan Mu, Jinglin Zhang, Sixian Chan, Shiqi Zhang, Hanting Yan, Shengyong Chen, Cong Bai

“…Comprehensive evaluations demonstrate that TCN M outperforms both existing deep learning methods and official meteorological forecasts across multiple metrics. …”
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Deep learning method for finding eigenpairs in Sturm-Liouville eigenvalue problems by Sen Zhang, Jian Zu, Jingqi Zhang

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Intelligent monitoring method for conveyor belt misalignment based on deep learning by ZUO Mingming, ZHANG Xi, YANG Zihao, SUN Qifei, ZHANG Mengchao, ZHANG Yuan, LI Hu

“…This paper proposed an intelligent monitoring method for conveyor belt misalignment based on deep learning. …”
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Faulty Links’ Fast Recovery Method Based on Deep Reinforcement Learning by Wanwei Huang, Wenqiang Gui, Yingying Li, Qingsong Lv, Jia Zhang, Xi He

“…Aiming to address the high recovery delay and link congestion issues in the communication network of Wide-Area Measurement Systems (WAMSs), this paper introduces Software-Defined Networking (SDN) and proposes a deep reinforcement learning-based faulty-link fast recovery method (DDPG-LBBP). …”
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An intelligent prediction method for rock core integrity based on deep learning by Zhaoxia Hu, Hua Mei, Lei Yu

“…Abstract To address the issue of serious inefficiency in the traditional manual evaluation methods of rock core integrity, a deep learning-based algorithm named IDA-RCF (Intelligent detection algorithm for Rock Core Fissure) is proposed in this paper, which realizes the automatic evaluation of rock core integrity in accordance with the fissure identification results. …”
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A Method of Fatigue Driving State Detection Based on Deep Learning by XIONG Qunfang, LIN Jun, YUE Wei

“…To this end, this paper put forward a fatigue recognition algorithm based on deep learning. Firstly, the face image feature points are automatic extracted using convolutional neural network and landmark algorithm. …”
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Deblurring Method of Face Recognition AI Technology Based on Deep Learning by Weilong Li, Jie Li, Junhui Zhou

“…As a common method of deep learning, a convolutional neural network (CNN) shows excellent performance in face recognition. …”
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Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Method by İbrahim Yücel Özbek, Mustafa Taha Güller, Zeynep Turanli Tosun, Nida Kumbasar, Özkan Miloğlu

“…This study aims to determine gender from hand-wrist radiographs using different deep-learning methods.Methods: The left hand-wrist radiographs of 1044 individuals (534 males and 510 females) were pre-processed to clarify the image and adjust the contrast. …”
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A Method for Detecting Foreign Objects in Pastries Based on Deep Learning by Haoqi TANG, Jun YANG, Rongchang CHEN

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Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation by S. Rashmi, S. Srinath, R. Rakshitha, B. V. Poornima

“…Abstract The study explores end-to-end deep learning frameworks and ensemble methods to enhance the accuracy of anatomical landmark identification in cephalometric radiographs, crucial for precise cephalometric analysis and effective orthodontic treatment planning. …”
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A Comprehensive Investigation of Anomaly Detection Methods in Deep Learning and Machine Learning: 2019–2023 by Shalini Kumari, Chander Prabha, Asif Karim, Md. Mehedi Hassan, Sami Azam

“…The outcome of this study focuses on various AD methods from 2019 to 2023. These techniques are categorized further into machine learning (ML), deep learning (DL), and federated learning (FL). …”
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