Convolution kernel of size 5 with arbitrary shape. by Xinwei Wang (352488)

Supplementary file 1_Optimizing quantum convolutional neural network architectures for arbitrary data dimension.pdf by Changwon Lee (20812727)

“…The number of input qubits determines the dimensions (i.e., the number of features) of the input data that can be processed, restricting the applicability of QCNN algorithms to real-world data. To address this issue, we propose a QCNN architecture capable of handling arbitrary input data dimensions while optimizing the allocation of quantum resources such as ancillary qubits and quantum gates. …”

EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

“…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …”

Percentage totBurden and percentage maxBurden reduced by all approaches for = 0.5345 in New Hampshire for FRED (first column) and SafeGraph (second column). by Jeffrey Keithley (14626551)

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FastGreedy, UnitGreedy, SingletonGreedy, 3-EnumGreedy, and POMS comparison with respect to practical running time (estimated for POMS) to achieve approximation guarantee for New Ha... by Jeffrey Keithley (14626551)

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Summary of greedy algorithms presented in this section. Details of approximation factors for FastGreedy and UnitGreedy may be found in [26] and [25], respectively. by Jeffrey Keithley (14626551)

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Percentage totBurden and percentage maxBurden reduced by UnitGreedy, SingletonGreedy, FastGreedy and baselines for = 0.535 in Iowa for FRED (first column) and SafeGraph (second col... by Jeffrey Keithley (14626551)

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Metapopulation model notation. by Jeffrey Keithley (14626551)

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Estimates of for each problem instance. by Jeffrey Keithley (14626551)

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The instance of MaxCasesAverted and MaxPeaksReduced is a graph <i>G</i> constructed from the given instance of Max k-SI. by Jeffrey Keithley (14626551)

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Percentage totBurden and percentage maxBurden reduced by UnitGreedy, FastGreedy and baselines for = 0.525 in Texas for FRED (first column) and SafeGraph (second column). by Jeffrey Keithley (14626551)

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Approximation factors for each problem instance. by Jeffrey Keithley (14626551)

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Environment ConFIGuration Information. by Xinwei Wang (352488)

“…An improved target detection algorithm is proposed to address these issues. The algorithm introduces AKConv into the C2F module. …”

Results of ablation experiment. by Xinwei Wang (352488)

“…An improved target detection algorithm is proposed to address these issues. The algorithm introduces AKConv into the C2F module. …”

Comparison diagram of mAP50. by Xinwei Wang (352488)

“…An improved target detection algorithm is proposed to address these issues. The algorithm introduces AKConv into the C2F module. …”

Improved YOLOv8s. by Xinwei Wang (352488)

“…An improved target detection algorithm is proposed to address these issues. The algorithm introduces AKConv into the C2F module. …”

YOLOv5s. by Xinwei Wang (352488)

“…An improved target detection algorithm is proposed to address these issues. The algorithm introduces AKConv into the C2F module. …”

Partial Training Images of the Dataset. by Xinwei Wang (352488)

“…An improved target detection algorithm is proposed to address these issues. The algorithm introduces AKConv into the C2F module. …”

LKA Network Structure. by Xinwei Wang (352488)

“…An improved target detection algorithm is proposed to address these issues. The algorithm introduces AKConv into the C2F module. …”

Comparison diagram of detection accuracy. by Xinwei Wang (352488)

“…An improved target detection algorithm is proposed to address these issues. The algorithm introduces AKConv into the C2F module. …”