Comparison of the curves of the DCIOU loss function and the CIOU loss function. by Xunqian Xu (21261899)

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FPS values of different methods on the three datasets. by Xunqian Xu (21261899)

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The network architecture of YOLOv8 comprises three parts. by Xunqian Xu (21261899)

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AP values of three loss functions on the three datasets, including four indicators: AP@50, AP@75, AP@M, and AP@L. by Xunqian Xu (21261899)

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AP values of three methods on the three datasets, including four indicators: AP @50, AP @75, AP @M, and AP @L. Experiment one is the baseline model without adding other modules, ex... by Xunqian Xu (21261899)

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Details the DLKA structure, which includes the DLKA-Attention module and the FFN module. The DLKA-Attention module mainly consists of the DLKA module, which comprises deformable de... by Xunqian Xu (21261899)

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AP values of different methods on the three datasets, including four indicators: AP@50, AP@75, AP@M, and AP@L. by Xunqian Xu (21261899)

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FPS values of different methods on the three datasets, where red represents the COCO dataset, yellow represents the MPII dataset, and green represents the HP dataset. by Xunqian Xu (21261899)

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Ap values of different methods on the three datasets. AP values include four indicators: AP@50, AP@75, AP@M, and AP@L. by Xunqian Xu (21261899)

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The decomposition diagram of the large kernel convolution, where the blue grid represents the convolution kernel and the green grid represents the center point. by Xunqian Xu (21261899)

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Illustrates the structure of the C2F-SimDLKA module. After processing with CBS, the features are first split into two parts: one part is retained without any processing, and the ot... by Xunqian Xu (21261899)

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Implementation code and computational results.  by Xunqian Xu (21261899)

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Source data for figures and tables. by Xunqian Xu (21261899)

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Datasheet1_Gait analysis comparison between manual marking, 2D pose estimation algorithms, and 3D marker-based system.pdf by Dimitrios Menychtas (16935831)

Algorithm operation steps. by Junyan Wang (4738518)

“…To address these issues, this paper proposes an improved object detection algorithm named SCI-YOLO11, which optimizes the YOLO11 framework from three aspects: feature extraction, attention mechanism, and loss function. …”

Supplementary file 1_Earthworm optimization algorithm for extracting parameters for solar cells and photovoltaic modules.docx by Fatima Wardi (22052360)

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Schematic diagram of the experimental algorithm. by Ronghua Meng (20978441)

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Flowchart of system algorithm. by Syed Zahurul Islam (9635163)

GELU function. by Yuanzhou Zheng (15195249)

Algorithm schematic diagram of the CSM module. by Huiying Zhang (200681)

“…The dynamic automated detection head DAIH improves the accuracy of infrared target detection by dynamically adjusting regression feature maps. Additionally, three innovative loss functions—focalerDIoU, focalerGIOU and focalerShapeIoU are proposed to reduce losses during the training process. …”