An artificial intelligence model for predicting an appropriate mAs with target exposure indicator for chest digital radiography by Jia-Ru Lin, Tai-Yuan Chen, Yu-Syuan Liang, Jyun-Jie Li, Ming-Chung Chou

“…However, estimating appropriate exposure factors before radiography with optimized image quality without overexposure or underexposure to patients is difficult. …”
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Fleet data based traffic modeling by Tamás Tettamanti, Levente Tőkés, Balázs Varga

“…By optimally scaling the Origin-Destination matrices of the sample fleet, an appropriate model can be approximated to provide traffic flow data beside average speeds. …”
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Design and Economic Analysis of Marine Vessel PV Power System Based on Solar Radiation Estimation by Batuhan Tural, Onur Akar

“…The Artificial Neural Network (ANN) model was trained by dividing it into training, validation and test data sets at a ratio of 70-15-15 and the performance of the model was obtained with average Mean Squared Error 0.00098 and Regression 0.99997. …”
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Classification of Fritillaria thunbergii appearance quality based on machine vision and machine learning technology by DONG Chengye, LI Dongfang, FENG Huaiqu, LONG Sifang, XI Te, ZHOU Qin’an, WANG Jun

“…The results showed that the model trained by the YOLO-X of YOLO (you only look once) series had relatively better performance. In addition, to optimize YOLO-X, according to the unique features of F. thunbergii dataset, a dilated convolution structure was embedded into the end of the backbone feature extraction network of YOLO-X as it could improve the model sensitivity to the dimension feature. …”
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Precision Target Spraying System Integrated with Remote Deep Learning Recognition Model for Cabbage Plant Centers by ZHANG Hui, HU Jun, SHI Hang, LIU Changxi, WU Miao

“…A Ghost-Backbone lightweight network structure was introduced, integrating remote sensing technologies along with the sprayer's forward speed and the frequency of spray responses. …”
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DualPFL: A Dual Sparse Pruning Method with Efficient Federated Learning for Edge-Based Object Detection by Shijin Song, Sen Du, Yuefeng Song, Yongxin Zhu

“…However, existing pruning algorithms exhibit high sensitivity to network architectures and typically require multiple sessions of retraining to identify optimal structures. …”
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Road‐Level Charging Gaps and Infrastructure Enhancements in Japan's Electric Vehicle Transition by Xiaoyan Xu, Yoshikuni Yoshida, Jiawei Yong, Shintaro Fukushima, Renhe Jiang, Yin Long

“…Among the alleviation measures, expanding the rapid charging network achieves the greatest reduction in charging insufficiency, decreasing the total length of roads with above‐average charging insufficiency by approximately 904.10 km across 51% of cities during rush hour. …”
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Robust face mask detection in complex scenarios using YOLOv8 and context-aware convolutions by Yingjie Wei, Huili Li, Yuanfei He, Li Li, Qiongshuai Lyu, Yu Yang

“…We also integrate the SENet attention mechanism to further optimize feature extraction efficiency. To improve the transmission of fine-grained face mask features within the network, we introduce context-aware convolutions in the Neck module, which facilitates the integration of contextual semantic information and enriches the feature details of small targets. …”
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DeepContainer: A Deep Learning-based Framework for Real-time Anomaly Detection in Cloud-Native Container Environments by Ke Xiong, Zhonghao Wu,  Xuzhong Jia

“…The proposed framework addresses critical security challenges in containerized infrastructures through an innovative integration of neural network architectures and automated response mechanisms. …”
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Traffic light detection and recognition based on deep learning for autonomous-rail rapid tram by XIONG Qunfang, LIN Jun, YUAN Xiwen, XU Yanghan, YUE Wei, LI Yuanzhengyu

“…These abnormal image data were saved and utilized for further training and optimizing the model. Experimental results reveals that the proposed approach effectively detected and recognized ART traffic lights, achieving an average detection precision of 84.76% on designated roads during the daytime while exhibiting good real-time performance.…”
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Multifunctional cells based neural architecture search for plant images classification by Lin Huang, Xi Qin, Tiejun Yang

“…Abstract To develop a high-performance convolutional neural network (CNN) model for plant image classification automatically, we propose a neural architecture search (NAS) method tailored to multifunctional cells (MFC), termed MFC-NAS. …”
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Geostatistics and Artificial Intelligence Applications for Spatial Evaluation of Bearing Capacity after Dynamic Compaction by Rodney Ewusi-Wilson, Junghee Park, Boyoung Yoon, Changho Lee

“…Data used in this study involve averaged SPT N value before dynamic compaction (Nbefore), averaged SPT N value after dynamic compaction (Nafter), applied energy (AE), X- and Y-coordinates at each borehole location, and degree of ground improvement (DI). …”
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An Improved UNet-Based Path Recognition Method in Low-Light Environments by Wei Zhong, Wanting Yang, Junhuan Zhu, Weidong Jia, Xiang Dong, Mingxiong Ou

“…Among the three attention mechanisms of channel attention, spatial attention, and combined attention, the most effective mechanism is identified. The optimal attention mechanism is incorporated into the optimized network to enhance the model’s ability to detect path edges and improve detection performance. …”
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Personalized trajectory inference framework integrating driving behavior recognition and temporal dependency learning. by Jinhao Yang, Junwen Cao, Mingyu Fang

“…The framework operates through three rigorously designed stages: (1)Data preprocessing involving kinematics feature extraction, (2)Driving style recognition utilizing acceleration variation rate and average time headway combined with K-Means++ traffic density clustering and K-neighbor Gaussian mixture model (K-GMM) analysis to classify driving behaviors into conservative, moderate, and radical categories, and (3)Personalized trajectory prediction employing a multi-level neural architecture with dedicated sub-networks for distinct driving styles. …”
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A Quadratic Speedup in Finding Nash Equilibria of Quantum Zero-Sum Games by Francisca Vasconcelos, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Panayotis Mertikopoulos, Georgios Piliouras, Michael I. Jordan

“…Recent developments in domains such as non-local games, quantum interactive proofs, and quantum generative adversarial networks have renewed interest in quantum game theory and, specifically, quantum zero-sum games. …”
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Fast QTMT partition decision based on deep learning by Shuang PENG, Xiaodong WANG, Zongju PENG, Fen CHEN

“…Compared with the predecessor standards, versatile video coding (VVC) significantly improves compression efficiency by a quadtree with nested multi-type tree (QTMT) structure but at the expense of extremely high coding complexity.To reduce the coding complexity of VVC, a fast QTMT partition method was proposed based on deep learning.Firstly, an attention-asymmetric convolutional neural network was proposed to predict the probability of partition modes.Then, the fast decision of partition modes based on the threshold was proposed.Finally, the cost of coding performance and time was proposed to obtain the optimal threshold, and the threshold decision method was proposed.Experimental results at different levels show that the proposed method achieves an average time saving of 48.62%/52.93%/62.01% with the negligible BDBR of 1.05%/1.33%/2.38%.Such results demonstrate that the proposed method significantly outperforms other state-of-the-art methods.…”
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The Extended Flexor Carpi Radialis Approach for Distal Radius Fracture Fixation: A Prospective Study by Sulaiman Alrefai, MD, Dionne Hsu, MD(c), Jonathan Persitz, MD, Atefeh Noori, PhD, Andrea Chan, MD, FRCSC, Ryan Paul, MD, FRCSC

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EMB-YOLO: A Lightweight Object Detection Algorithm for Isolation Switch State Detection by Haojie Chen, Lumei Su, Riben Shu, Tianyou Li, Fan Yin

“…Firstly, we propose an efficient mobile inverted bottleneck convolution (EMBC) module for the backbone network. This module is designed with a lightweight structure, aimed at reducing the computational complexity and parameter count, thereby optimizing the model’s computational efficiency. …”
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PBX micro defect characterization by using deep learning and image processing of micro CT images by Liang-liang Lv, Wei-bin Zhang, Xiao-dong Pan, Gong-ping Li, Cui Zhang

“…We optimize the structure of skip connection in PBX_SegNet and introduce a concurrent spatial and channel squeeze and excitation (SCSE) module on each stage in the encoder network and in the decoder network. …”
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Aging-Invariant Sheep Face Recognition Through Feature Decoupling by Suhui Liu, Chuanzhong Xuan, Zhaohui Tang, Guangpu Wang, Xinyu Gao, Zhipan Wang

“…To address this limitation, we propose the lifelong biometric learning of the sheep face network (LBL-SheepNet), a feature decoupling network designed for continuous adaptation to ovine facial changes, and constructed a dataset of 31,200 images from 55 sheep tracked monthly from 1 to 12 months of age. …”
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