Visualization of algorithm detection results. حسب Xinpeng Yao (18882573)

"…On the KITTI dataset, our algorithm achieved 3D average detection accuracy (AP3D) of 81.15%, 62.02%, and 58.68% across three difficulty levels. …"

An overview of the organization of the study program. حسب Marialuisa Gandolfi (8639238)

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Overview of the development of the biomarkers in the motor, exteroceptive, interoceptive, and cerebral domains. حسب Marialuisa Gandolfi (8639238)

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The schedule of enrolment, interventions, and assessments. حسب Marialuisa Gandolfi (8639238)

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(A) Illustration of grouping and segmentation based on the global similarity structure when the number of elements is small. A, B, C, and D represent stimulus elements at different... حسب Yen-Ju Chen (354876)

Parameters of stimuli used in the study. حسب Elnaz Nemati (21402730)

"…<div><p>This study introduces a neurobiologically inspired computational model based on the predictive coding algorithm, providing insights into coherent motion detection processes. …"

Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived... حسب Quang Dung Dinh (20995766)

The run time for each algorithm in seconds. حسب Edward Antonian (21453161)

"…The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. Next, we examine the statistical effect of correlated prediction error and propose a method for Generalized Least Squares (GLS) on graphs. …"

A classification scheme of bipartite randomization algorithms, based on whether the matrix row and columns sums are preserved exactly (Fixed, <i>F</i>), preserved on average (Propo... حسب Zachary P. Neal (9946331)

Example gauge chart outputs produced by the M.E.D.V.I.S. algorithm. حسب Hector Torres (11708207)

Execution time comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset. حسب Liyan Sun (760586)

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F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DNME 1000 dataset. حسب Liyan Sun (760586)

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Genes of the epistastic interactions detected on the seven GWAS data using Epi-SSA. حسب Liyan Sun (760586)

الموضوعات:

Power comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset. حسب Liyan Sun (760586)

الموضوعات:

Execution time comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 100 dataset. حسب Liyan Sun (760586)

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The brief description on the WTCCC dataset. حسب Liyan Sun (760586)

الموضوعات:

F-measure comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DME 1000 dataset. حسب Liyan Sun (760586)

الموضوعات:

Power comparisons between AntEpiSeeker(A), DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B), SNPHarvester(H), SNPRuler(R) and Epi-SSA(P) on the DNME 1000 dataset. حسب Liyan Sun (760586)

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The overall structure and execution flow of Epi-SSA. حسب Liyan Sun (760586)

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Gene pairs of the epistastic interactions detected on the seven GWAS data using Epi-SSA. حسب Liyan Sun (760586)

الموضوعات: