FP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n by Ke Rao, Fengxia Zhao, Tianyu Shi

“…Additionally, it incorporates the decoupled fully connected (DFC) attention mechanism, which minimizes information loss during long-range feature transmission by separately capturing pixel information along horizontal and vertical axes via convolution. Second, the Dynamic ATSS label allocation strategy is applied, which dynamically adjusts label assignments by integrating Anchor IoUs and predicted IoUs, effectively reducing the misclassification of high-quality prediction samples as negative samples. …”
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ARSOD-YOLO: Enhancing Small Target Detection for Remote Sensing Images by Yijuan Qiu, Xiangyue Zheng, Xuying Hao, Gang Zhang, Tao Lei, Ping Jiang

“…Moreover, the Adaptive Multi-scale Convolution Kernel Feature Fusion Module (AKSFFM) enhances feature fusion through multi-scale convolution operations and attention weight learning mechanisms. …”
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LKD-YOLOv8: A Lightweight Knowledge Distillation-Based Method for Infrared Object Detection by Xiancheng Cao, Yueli Hu, Haikun Zhang

“…Linear deformable convolution (LDConv) strengthens spatial feature extraction by dynamically adjusting kernel offsets, while coordinate attention (CA) refines feature alignment through channel-wise interaction. …”
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CKAN-YOLOv8: A Lightweight Multi-Task Network for Underwater Target Detection and Segmentation in Side-Scan Sonar by Yao Xiao, Hualong Yang, Dongchen Dai, Hongjian Wang, Ziqi Shan, Hao Wu

“…This paper proposes CKAN-YOLOv8, a lightweight multi-task network integrating Kolmogorov–Arnold Networks Convolution (KANConv) into YOLOv8. The core innovation replaces conventional convolutions with KANConv blocks using learnable B-spline activations, dynamically adapting to noise and multi-scale targets while ensuring parameter efficiency. …”
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Improved U-Net for Precise Gauge Dial Segmentation in Substation Inspection Systems: A Study on Enhancing Accuracy and Robustness by Wan Zou, Yiping Jiang, Wenlong Liao, Songhai Fan, Yueping Yang, Jin Hou, Hao Tang

“…Additionally, we replace traditional convolution operations with wavelet convolution, which improves the network’s ability to capture low-frequency information, essential for understanding the overall dial structure. …”
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An Efficient Aerial Image Detection with Variable Receptive Fields by Wenbin Liu, Liangren Shi, Guocheng An

“…Based on the RT-DETR architecture, our approach introduces three key innovations: the multi-scale receptive field adaptive fusion (MSRF²) module replaces the Transformer encoder with parallel dilated convolutions and spatial-channel attention to adjust receptive fields for confusing objects dynamically; the gated multi-scale context (GMSC) block reconstructs the backbone using Gated Multi-Scale Context units with attention-gated convolution (AGConv), reducing parameters while enhancing multi-scale feature extraction; and the context-guided fusion (CGF) module optimizes feature fusion via context-guided weighting to resolve multi-scale semantic conflicts. …”
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Red Tide Detection Method Based on a Time Series Fusion Network Model: A Case Study of GOCI Data in the East China Sea by Tianhong Ding, Zhiqiang Xu, Yunjie Wang, Qinglian Hou, Xiangyong Liu, Fengshuang Ma

“…A novel feature extraction module, ASPC-DSC, combines atrous spatial pyramid convolution with depthwise separable convolution to effectively fuse multi-scale contextual features while improving computational efficiency. …”
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CrossModalSync: joint temporal-spatial fusion for semantic scene segmentation in large-scale scenes by Shuyi Tan, Yi Zhang, Yan Li, Byeong-Seok Shin

“…Abstract Owing to its ability to enable precise perception of dynamic and complex environments, point cloud semantic segmentation has become a critical task for autonomously driven vehicles in recent years. …”
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SYNTHESIS OF MOBILE OBJECTS COMPROMISABLE OPTIMAL TRAJECTORIES IN THE CONFLICT ENVIRONMENT by Albert M. Voronin, Yurii K. Ziatdinov, Oleksandr Y. Permiakov, Ihor D. Varlamov

“…In this regard, the problem of optimal movement trajectory synthesis under given conditions is solved by the dynamic programming method with optimality criterion obtained by as nonlinear compromise scheme scalar convolution. …”
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Vibration under variable magnitude moving distributed masses of non-uniform Bernoulli-Euler beam resting on Pasternak elastic foundation by T. O. Awodola, S. A. Jimoh, B. B. Awe

“…The dynamic response to variable magnitude moving distributed masses of simply supported non-uniform Bernoulli-Euler beam resting on Pasternak elastic foundation is investigated in this paper. …”
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Exposed conductor detection of 10 kV distribution line based on improved YOLOv8 by Qiwen JING, Sipeng HAO, Siyuan LI

“…The algorithm replaces the original convolution with omni-dimensional dynamic convolution in the backbone network, enhancing the features of exposed conductors through multi-dimensional feature extraction. …”
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DP-YOLO: A Lightweight Real-Time Detection Algorithm for Rail Fastener Defects by Lihua Chen, Qi Sun, Ziyang Han, Fengwen Zhai

“…First, we design a Depthwise Separable Convolution Stage Partial (DSP) module that integrates depthwise separable convolution with a CSP residual connection strategy, reducing model parameters while enhancing recognition accuracy. …”
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Efficient vision transformers with edge enhancement for robust small target detection in drone-based remote sensing by Xuguang Zhu, Zhizhao Zhang

“…First, a Multi-Scale Edge Enhancement Fusion (MSEEF) module is designed, integrating adaptive pooling and edge-aware convolution to preserve target boundary details while enabling cross-scale feature interaction. …”
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Fast and Accurate Density Estimation of Hybrid Rice Seedlings Using a Smartphone and an Improved YOLOv8 Model by Zehua Li, Yongjun Lin, Yihui Pan, Xu Ma, Xiaola Wu

“…Secondly, the Standard Convolution (SConv) layers in the neck network were replaced by the Group Shuffle Convolution (GSConv) layer to lightweight the model. …”
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Gesture Recognition Achieved by Utilizing LoRa Signals and Deep Learning by Peihao Zhang, Baofeng Zhao

“…Through the combination of residual learning and dynamic convolution techniques, the SS-ResNet50 model significantly enhances the extraction capability of multi-scale gesture features, thereby augmenting the classification accuracy. …”
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A Computational Fractional Signal Derivative Method by Matías Salinas, Rodrigo Salas, Diego Mellado, Antonio Glaría, Carolina Saavedra

“…The proposal consists of a new interpretation of the Grünwald–Letnikov differintegral operator where we have introduced a finite Cauchy convolution with the Grünwald–Letnikov dynamic kernel. …”
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Parallelizing analog in-sensor visual processing with arrays of gate-tunable silicon photodetectors by Zheshun Xiong, Wen Liang, Meiyue Zhang, Dacheng Mao, Qiangfei Xia, Guangyu Xu

“…Furthermore, their bipolar analog output captures the amplitude of event-driven light changes and the spatial convolution of optical power densities at the device level, a feature that helps boost their performance in classifying dynamic motions and static images. …”
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CGADNet: A Lightweight, Real-Time, and Robust Crosswalk and Guide Arrow Detection Network for Complex Scenes by Guangxing Wang, Tao Lin, Xiwei Dong, Longchun Wang, Qingming Leng, Seong-Yoon Shin

“…In this study, we incorporated a novel C2f_Van module based on VanillaBlock, employed depth-separable convolution to reduce the parameters efficiently, utilized partial convolution (PConv) for lightweight FasterDetect, and utilized a bounding box regression loss with a dynamic focusing mechanism—WIoU<i>_v3</i>—to enhance the detection performance. …”
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A multimodal functional structure-based graph neural network for fatigue detection by Dongrui Gao, Zhihong Zhou, Zongyao Peng, Haokai Zhang, Shihong Liu, Manqing Wang, Hongli Chang

“…An innovative intra- and inter-channel separable convolution module is designed to extract deep interaction patterns through parallel convolution operations within and across signal channels. …”
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Robust scale fusion and edge-aware feature attention network for remote sensing UAV road detection under harsh weather by Jialang Liu, Jialei Zhan, Jiehua Zhang, Jiangming Chen, Yan Song, Lixing Tang, Le Zhou, Chengsi Du, Yingmei Wei, Yanming Guo

“…RSFC dynamically adjusts convolution kernels to better handle scale variation and degraded visual inputs, while EAFA enhances edge information and suppresses noise in challenging environments. …”
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