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

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Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

3D modeling qualities of the AS single-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

3D modeling qualities of the AM multiple-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

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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Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…Hierarchical clustering was computed using the scikit learn module in Python. C) Dendrogram of averaged functional connectivity from healthy subjects. …”

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

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Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

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

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Implementation code and computational results.  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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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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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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Source data for figures and tables. 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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PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

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