IVP-YOLOv5: an intelligent vehicle-pedestrian detection method based on YOLOv5s by Yang Sun, Jiankun Song, Yong Li, Yi Li, Song Li, Zehao Duan

“…Computer vision is now vital in intelligent vehicle environment perception systems. …”
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CMRNet: An Automatic Rapeseed Counting and Localization Method Based on the CNN-Mamba Hybrid Model by Jie Li, Chenbo Yang, Chengyong Zhu, Tao Qin, Jingmin Tu, Binhui Wang, Jian Yao, Jiangwei Qiao

“…The model synergizes local feature extraction via CNN with the global modeling strengths of the Mamba state space model, yielding semantically rich features while significantly enhancing computational efficiency and inference speed. …”
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A turbulence reduced order model based on non-interpolated convolutional autoencoder by WU Pin, ZHANG Bo, SONG Chao, ZHOU Zhu

“…This paper introduces an innovative solution: a non-interpolated convolutional autoencoder, designed to extract nonlinear features from the flow field while curbing parameter count, evading interpolation errors, and mitigating additional computational burdens. …”
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A wave-resolving two-dimensional vertical Lagrangian approach to model microplastic transport in nearshore waters based on TrackMPD 3.0 by I. Jalón-Rojas, D. Sous, D. Sous, V. Marieu

“…This approach introduces novel features such as coupling with advanced turbulence models, simulating resuspension and bedload processes, implementing advanced settling and rising velocity formulations, and enabling parallel computation. …”
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Underground personnel detection and tracking using improved YOLOv7 and DeepSORT by Weiqiang FAN, Xuejin WANG, Yinghui ZHANG, Xiaoyu LI

“…Compared with YOLOv7-DeepSORT algorithm, the number of network parameters of the improved algorithm is reduced by 36%, significantly improving the real-time performance of underground multi personnel target detection and tracking, and is expected to be deployed in the underground intelligent edge computing monitoring platform.…”
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Development of a data-driven neural network model for electron thermal transport in NSTX by H. Chung, C.Y. Lee, G.J. Choi, S.M. Kaye, B.P. LeBlanc, J.W. Berkery, Y.-S. Na

“…A data-driven electron thermal transport neural network (ETT-NN) model, trained on TRANSP interpretative analysis results of National Spherical Torus Experiment (NSTX), was developed to enable faster and more accurate ETT computation for spherical tokamaks (STs). The model incorporates both convolutional NNs and recurrent NNs, allowing it to simultaneously account for the spatial and temporal non-localities and multi-scale features of turbulent transport, which have been considered only in a limited manner in conventional models. …”
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Lightweight multilayer interactive attention network for aspect-based sentiment analysis by Wenjun Zheng, Shunxiang Zhang, Cheng Yang, Peng Hu

“…Such correlation degree is calculated by multiple computational layers with neural attention models. Third, we use a parameter-sharing strategy among the computational layers. …”
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Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy by Eyachew Misganew Tegaw, Betelhem Bizuneh Asfaw

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Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks by Kun Mei, Zikang Feng, Hui Liu, Min Wang, Chao Ce, Shi Yin, Xiaoying Zhang, Bin Wang

“…Regions of interest (ROIs) within the CT lung window level were manually delineated using ITK-SNAP software, enabling the extraction of relevant CT imaging features, including morphological descriptors, first-order statistical parameters, texture attributes, and high-order characteristics. …”
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In-silico platform for the multifunctional design of 3D printed conductive components by Javier Crespo-Miguel, Sergio Lucarini, Sara Garzon-Hernandez, Angel Arias, Emilio Martínez-Pañeda, Daniel Garcia-Gonzalez

“…This work provides a multi-scale computational framework to evaluate the thermo-electro-mechanical behaviour of printed conductive polymers. …”
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A Defect Detection Algorithm for Optoelectronic Detectors Utilizing GLV-YOLO by Xinfang Zhao, Qinghua Lyu, Hui Zeng, Zhuoyi Ling, Zhongsheng Zhai, Hui Lyu, Saffa Riffat, Benyuan Chen, Wanting Wang

“…The experimental results showed that the proposed algorithm achieved 98.9% accuracy, with 2.1 million parameters and a computational cost of 7.0 GFLOPs. Compared to other methods, our approach outperforms them in both performance and efficiency, fulfilling the real-time and precise defect detection needs of photodetectors.…”
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Enhanced IoT-Based Face Mask Detection Framework Using Optimized Deep Learning Models: A Hybrid Approach With Adaptive Algorithms by Parul Dubey, Pushkar Dubey, Celestine Iwendi, Cresantus N. Biamba, Deepak Dasaratha Rao

“…So that the model can take full advantage of computing capacity and still operate in real time on devices with limited resources. …”
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Machine learning and complex network analysis of drug effects on neuronal microelectrode biosensor data by Manuel Ciba, Marc Petzold, Caroline L. Alves, Francisco A. Rodrigues, Yasuhiko Jimbo, Christiane Thielemann

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Classification of shale gas “sweet spot” based on Random Forest machine learning by NIE Yunli, GAO Guozhong

“…Firstly, data from ten wells in Changning area are selected and eleven features are selected for “sweet spot” classification by the Kendall correlation. …”
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Ground Fissure Identification in Mining Areas from UAV Images Based on DN-CAMSCBNet by Haibin Hu, Xinhui Guo, Jie Xiao

“…These are used to enhance its ability to capture complex image features, expand the receptive field of the original model, reduce the number of parameters, and reduce computational complexity. …”
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Optimized Deep Neural Network for High-Precision Psoriasis Classification from Dermoscopic Images by Charu Bolia, Sunil Joshi

“…This compact design with low trainable parameters reduces the computational time and memory makes the model well-suited for deployment for portable devices and enabling real-time mobile-based dermatological assessments. …”
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Improved YOLOv10 for Visually Impaired: Balancing Model Accuracy and Efficiency in the Case of Public Transportation by Rio Arifando, Shinji Eto, Tibyani Tibyani, Chikamune Wada

“…The model also exhibits reduced computational complexity and storage requirements, highlighting its efficiency. …”
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OW-YOLO: An Improved YOLOv8s Lightweight Detection Method for Obstructed Walnuts by Haoyu Wang, Lijun Yun, Chenggui Yang, Mingjie Wu, Yansong Wang, Zaiqing Chen

“…Additionally, the model’s parameter count decreased by 49.2%, weight file size was reduced by 48.1%, and computational load dropped by 37.3%, effectively mitigating the impact of obstruction on detection accuracy. …”
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ES-UNet: efficient 3D medical image segmentation with enhanced skip connections in 3D UNet by Minyoung Park, Seungtaek Oh, Junyoung Park, Taikyeong Jeong, Sungwook Yu

“…Methods We propose ES-UNet, a 3D segmentation architecture that achieves superior segmentation performance while offering competitive efficiency across multiple computational metrics, including memory usage, inference time, and parameter count. …”
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Steel Surface Defect Detection Technology Based on YOLOv8-MGVS by Kai Zeng, Zibo Xia, Junlei Qian, Xueqiang Du, Pengcheng Xiao, Liguang Zhu

“…Compared with YOLOv8n from experimental results, the average accuracy, recall rate, and frames per second of the improved model were improved by 5.2%, 10.5%, and 6.4%, respectively, while the number of parameters and computational costs were reduced by 5.8% and 14.8%, respectively. …”
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