The expert screening cost <i>g</i>_expert(<i>x</i>) defined for the Challenge: Mean cost for screening a fraction <i>x</i> of a patient cohort for cardiac abnormalities. حسب Matthew A. Reyna (16965038)

الموضوعات:

Local topological scales of hierarchical community organization in structural and functional brain graphs. حسب Arian Ashourvan (6685232)

Comparison between simulations for all algorithms (success rate <i>versus</i> number of swarm particles). حسب Rutinaldo Aguiar Nascimento (14259594)

الموضوعات:

Summary of the contrasts obtained from the normalized images for both inclusions as a function of the host type and the wavelength. حسب María Victoria Waks-Serra (21578611)

Fraction of stripes considered as a function of aspect ratio cut-off value for individual stripe measurements. حسب Pratik Mullick (12851011)

الموضوعات:

Overall concept and specific components for developing the cloud based solution. حسب Vlad Ploscaru (13767257)

الموضوعات: "…artificial intelligence algorithms…"

Cycle GAN approach for performing style transfer between healthy and pathological coronary angiography images slices. حسب Vlad Ploscaru (13767257)

الموضوعات: "…artificial intelligence algorithms…"

Sample envisaged detection of the distal point (white circle) for a right coronary artery image. حسب Vlad Ploscaru (13767257)

الموضوعات: "…artificial intelligence algorithms…"

Approach for artificial intelligence based virtual post-percutaneous coronary intervention fractional flow reserve (FFR) computation. حسب Vlad Ploscaru (13767257)

الموضوعات: "…artificial intelligence algorithms…"

Fig 1 - حسب Vlad Ploscaru (13767257)

الموضوعات: "…artificial intelligence algorithms…"

Graphic processing unit instance orchestration on the cloud. حسب Vlad Ploscaru (13767257)

الموضوعات: "…artificial intelligence algorithms…"

Flowchart of the general algorithm for one trial. حسب Junying Wang (509009)

Explained variance ration of the PCA algorithm. حسب Abeer Aljohani (18497914)

"…<div><p>Chest X-ray image classification plays an important role in medical diagnostics. Machine learning algorithms enhanced the performance of these classification algorithms by introducing advance techniques. …"

RMSE results. حسب YueSheng Jiang (19267984)

"…To overcome these limitations, this paper developed a simple and fast adaptive remote sensing image Spatio-Temporal fusion method based on Fit-FC, called Adapt Lasso-Fit-FC (AL-FF). Firstly, the sparse characteristics of time phase change between images are explored, and a time phase change estimation model based on sparse regression is constructed, which overcomes the fuzzy problem of fusion image caused by the failure of linear regression to capture complex nonlinear time phase transition in the weighted Function method, making the algorithm better at capturing details. …"

Results of the Kherson Area Visual Assessment. حسب YueSheng Jiang (19267984)

"…To overcome these limitations, this paper developed a simple and fast adaptive remote sensing image Spatio-Temporal fusion method based on Fit-FC, called Adapt Lasso-Fit-FC (AL-FF). Firstly, the sparse characteristics of time phase change between images are explored, and a time phase change estimation model based on sparse regression is constructed, which overcomes the fuzzy problem of fusion image caused by the failure of linear regression to capture complex nonlinear time phase transition in the weighted Function method, making the algorithm better at capturing details. …"

Work flow chart. حسب YueSheng Jiang (19267984)

"…To overcome these limitations, this paper developed a simple and fast adaptive remote sensing image Spatio-Temporal fusion method based on Fit-FC, called Adapt Lasso-Fit-FC (AL-FF). Firstly, the sparse characteristics of time phase change between images are explored, and a time phase change estimation model based on sparse regression is constructed, which overcomes the fuzzy problem of fusion image caused by the failure of linear regression to capture complex nonlinear time phase transition in the weighted Function method, making the algorithm better at capturing details. …"

Experimental data. حسب YueSheng Jiang (19267984)

"…To overcome these limitations, this paper developed a simple and fast adaptive remote sensing image Spatio-Temporal fusion method based on Fit-FC, called Adapt Lasso-Fit-FC (AL-FF). Firstly, the sparse characteristics of time phase change between images are explored, and a time phase change estimation model based on sparse regression is constructed, which overcomes the fuzzy problem of fusion image caused by the failure of linear regression to capture complex nonlinear time phase transition in the weighted Function method, making the algorithm better at capturing details. …"

Results of the PY area visual assessment. حسب YueSheng Jiang (19267984)

"…To overcome these limitations, this paper developed a simple and fast adaptive remote sensing image Spatio-Temporal fusion method based on Fit-FC, called Adapt Lasso-Fit-FC (AL-FF). Firstly, the sparse characteristics of time phase change between images are explored, and a time phase change estimation model based on sparse regression is constructed, which overcomes the fuzzy problem of fusion image caused by the failure of linear regression to capture complex nonlinear time phase transition in the weighted Function method, making the algorithm better at capturing details. …"

Main parameters of braking system. حسب Honglei Pang (22693724)

الموضوعات:

Simulation Results Plot of the SBW System Response: (a) Step response curve of the SBW system; (b) Sine response curve of the SBW system; (c) Steady state error curve of the SBW sy... حسب Honglei Pang (22693724)

الموضوعات: