Advancing Ton-Bag Detection in Seaport Logistics with an Enhanced YOLOv8 Algorithm by Xiulin Qiu, Haozhi Zhang, Chang Yuan, Qinghua Liu, Hongzhi Yao

“…Then, with reference to spatial and channel reconstruction convolution and deformable convolution, the C2f-SCTT block is designed for the backbone network, which reduces the spatial and channel redundancy between features in the network. …”
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MXT-YOLOv7t: An Efficient Real-Time Object Detection for Autonomous Driving in Mixed Traffic Environments by Afdhal Afdhal, Khairun Saddami, Mirshal Arief, Sugiarto Sugiarto, Zahrul Fuadi, Nasaruddin Nasaruddin

“…Therefore, the proposed model effectively performs real-time detection in complex traffic scenarios, offering a lightweight design with high detection accuracy, fast inference times, and minimal computational cost.…”
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StomaYOLO: A Lightweight Maize Phenotypic Stomatal Cell Detector Based on Multi-Task Training by Ziqi Yang, Yiran Liao, Ziao Chen, Zhenzhen Lin, Wenyuan Huang, Yanxi Liu, Yuling Liu, Yamin Fan, Jie Xu, Lijia Xu, Jiong Mu

“…Our findings underscore the superior detection capabilities of StomaYOLO compared to existing methods, offering a cost-effective solution that is suitable for practical implementation. …”
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Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

“…The colorimetric method, due to its rapid and low-cost characteristics, demonstrates a wide range of application prospects in on-site water quality testing. …”
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SAM-CTMapper: Utilizing segment anything model and scale-aware mixed CNN-Transformer facilitates coastal wetland hyperspectral image classification by Jiaqi Zou, Wei He, Haifeng Wang, Hongyan Zhang

“…Additionally, existing methods encounter difficulties in practical wetland classification tasks due to the high cost of hyperspectral wetland data labeling. This paper introduces SAM-CTMapper, a coastal wetland classification framework that incorporates a scale-aware mixed CNN-Transformer (CTMapper) to precisely identify wetland cover types using hyperspectral images, and the advanced segment anything model (SAM) to save labor costs in data labeling. …”
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DMCF-Net: Dilated Multiscale Context Fusion Network for SAR Flood Detection by Zhimin Wang, Lingli Zhao, Nan Jiang, Weidong Sun, Jie Yang, Lei Shi, Hongtao Shi, Pingxiang Li

“…DFR module uses convolutions with varying kernel sizes to refine the deepest features, improving the accuracy of flood detection. …”
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MFFCI–YOLOv8: A Lightweight Remote Sensing Object Detection Network Based on Multiscale Features Fusion and Context Information by Sheng Xu, Lin Song, Junru Yin, Qiqiang Chen, Tianming Zhan, Wei Huang

“…The experimental results demonstrate that our model offers a low computational cost and high detection accuracy compared to other RSOD models and other YOLO models.…”
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A Lightweight Model for Weed Detection Based on the Improved YOLOv8s Network in Maize Fields by Jinyong Huang, Xu Xia, Zhihua Diao, Xingyi Li, Suna Zhao, Jingcheng Zhang, Baohua Zhang, Guoqiang Li

“…Finally, Dualconv was employed instead of the conventional convolution for downsampling, further diminishing the network load. …”
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YOLO-WTB: Improved YOLOv12n Model for Detecting Small Damage of Wind Turbine Blades From Aerial Imagery by Phat T. Nguyen, Duy C. Huynh, Loc D. Ho, Matthew W. Dunnigan

“…Wind energy has been extensively studied worldwide to advance technology, reduce operating costs, and improve performance. A key challenge in this field is ensuring the optimal performance of wind turbines through proactive and effective maintenance strategies. …”
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FP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n by Ke Rao, Fengxia Zhao, Tianyu Shi

“…Lastly, an asymmetric small-target detection head, FADH, is proposed to utilize depth-separable convolution to accomplish classification and regression tasks, enabling more precise capture of detailed information across scales and improving the detection of small-target defects. …”
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YOLO-SRMX: A Lightweight Model for Real-Time Object Detection on Unmanned Aerial Vehicles by Shimin Weng, Han Wang, Jiashu Wang, Changming Xu, Ende Zhang

“…Secondly, within the neck network, multi-scale feature extraction is facilitated through the design of novel composite convolutions, ConvX and MConv, based on a “split–differentiate–concatenate” paradigm. …”
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Random Undersampled Digital Elevation Model Super-Resolution Based on Terrain Feature-Aware Deep Learning Network by Ziqiang Huo, Meng Xi, Jingyi He, Zhengjian Li, Jiabao Wen

“…However, due to the limitation of measurement cost and complex terrain, the collected DEMs often have randomly missing undersampled points and low sampling density. …”
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Two-Stage Locating and Capacity Optimization Model for the Ultra-High-Voltage DC Receiving End Considering Carbon Emission Trading and Renewable Energy Time-Series Output Reconstru... by Lang Zhao, Zhidong Wang, Hao Sheng, Yizheng Li, Tianqi Zhang, Yao Wang, Haifeng Yu

“…Then, a carbon emission trading cost (CET) model is constructed based on the CET mechanism, and the two-stage locating and capacity optimization model for the UHV DC receiving end is proposed under the constraint of dispatch safety and stability. …”
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MSAN-Net: An End-to-End Multi-Scale Attention Network for Universal Industrial Defect Detection by Zelu Wang, Ming Luo, Xinghe Xie, Yue Sun, Xinyu Tian, Zhengxuan Chen, Junwei Xie, Qinquan Gao, Tong Tong, Yue Liu, Tao Tan

“…MSAN-Net was adopted an integrated architecture, deeply combining UnifiedViT, C2f modules, convolution operations, SPPF structure, and Bi-Level Routing Attention mechanism to achieve accurate identification of complex industrial defects. …”
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Generating synthetic brain PET images of synaptic density based on MR T1 images using deep learning by Xinyuan Zheng, Patrick Worhunsky, Qiong Liu, Xueqi Guo, Xiongchao Chen, Heng Sun, Jiazhen Zhang, Takuya Toyonaga, Adam P. Mecca, Ryan S. O’Dell, Christopher H. van Dyck, Gustavo A. Angarita, Kelly Cosgrove, Deepak D’Souza, David Matuskey, Irina Esterlis, Richard E. Carson, Rajiv Radhakrishnan, Chi Liu

“…Methods We implemented a convolution-based 3D encoder-decoder to predict [11C]UCB-J SV2A PET images. …”
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Online evaluation method for MMC submodule capacitor aging based on CapAgingNet by Xinlan Deng, Youhan Deng, Liang Qin, Weiwei Yao, Min He, Kaipei Liu

“…Moreover, existing online approaches require additional sampling channels, thereby increasing system complexity and costs. To address these issues, this paper proposes an online evaluation method for submodule capacitor aging based on CapAgingNet. …”
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Research on lightweight malware classification method based on image domain by SUN Jingzhang, CHENG Yinan, ZOU Binghui, QIAO Tonghua, FU Sizheng, ZHANG Qi, CAO Chunjie

“…To address the high deployment costs and long prediction times associated with traditional malware classification methods, a lightweight malware visualization classification method was proposed. …”
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An improved lightweight method based on EfficientNet for birdsong recognition by Haolun He, Hui Luo

“…Abstract In the context of birdsong recognition, conventional modeling approaches often involve a significant number of parameters and high computational costs, rendering them unsuitable for deployment in embedded field monitoring devices. …”
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Intelligent Detection Algorithm for Concrete Bridge Defects Based on SATH–YOLO Model by Lanlin Zou, Ao Liu

“…Lastly, a lightweight TDMDH detection head with shared convolution and dynamic feature selection further reduced computational costs. …”
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The Cultural Value Validity of Digital Media Art Based on Deep Learning Network Model by Yuan Ruan

“…However, in the face of an increasing number of digital media art works, the identification of artistic and cultural value is mainly done manually by professionals, which costs a lot of human and financial resources. Therefore, it is of great practical significance to study how to efficiently and accurately classify various types of artistic images to help users select images that meet their needs. …”
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