Comparison of edge-weight estimation performance for simulations with three conditions.

Comparing edge detection techniques.

Katrina K. Treloar (425532)
Matthew J. Simpson (425533)

June 2013

Comparing three edge detection techniques for barrier assays with two different cell densities: 1...

Inferred vs. simulated weights for three simulated observers.

Ana Radonjić (6585683)
Nicolas P. Cottaris (6585686)
David H. Brainard (349665)

April 2019

The simulated observer color-material weights are shown in green (identical to those shown for corre...

Comparative evaluation of three algorithms in overall orientation of the synthetic phenotype network.

Huange Wang (619576)
Fred A. van Eeuwijk (358696)

August 2014

Sample size, means and standard deviations of the proportion of true positive edges that were cor...

Comparison of edge-weight estimation performance for simulations with three conditions.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

Top and bottom rows respectively correspond to the SSE of methods in scenario (S1) and scenario (S2)...

Comparison of edge-weight estimation performance for simulations studying effect of ordering.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

Top row corresponds to scenario (S5) which has three conditions, and the next two rows correspond to...

Comparison of edge detection performance for simulations with three conditions.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

Top and bottom rows respectively correspond to the precision-recall curves in scenario (S1) and scen...

Performance comparison for simulation with 3 conditions.

Yafei Lyu (4544320)
Lingzhou Xue (3617093)
Feipeng Zhang (4498429)
Hillary Koch (5778071)
Laura Saba (74165)
Katerina Kechris (436022)
Qunhua Li (484957)

October 2018

Top row (A-D): ROC curve for edge detection for the settings of S1-S4; Bottom row (E-H): SSE for edg...

Comparison of edge detection performance for simulations with four conditions.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

Top and bottom rows respectively correspond to the ROC curves in scenario (S3) and scenario (S4). Th...

Comparison of run-time for simulations with three and four conditions.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

Top row corresponds to the run-times in seconds of different methods in scenario (S1) and scenario (...

Comparison of edge-preserving performance on a natural image.

Xueshun Pang (5665183)
Suqi Zhang (797690)
Junhua Gu (797691)
Lingling Li (427154)
Boying Liu (797692)
Huaibin Wang (797693)

September 2015

(a) The natural image, results by (b) LGM (λ = 0.35), and (c) ILGM(λ = 0.0035). (d)...

Edge Weight Distributions.

Matthew Burgess (2802568)
Eytan Adar (6156)
Michael Cafarella (2802571)

May 2016

Histogram of edge weights on a benchmark graph with μ = 0.4 and 20% of the edges removed: ...

Edge weight calculations, for the arched and slanted streamline paths of Fig 4, as a function of seed point density.

Luis M. Colon-Perez (769593)
Caitlin Spindler (769594)
Shelby Goicochea (769595)
William Triplett (769596)
Mansi Parekh (769597)
Eric Montie (238233)
Paul R. Carney (131055)
Catherine Price (769598)
Thomas H. Mareci (481562)

July 2015

The seed point density is P = n3, where n = 1, 3, 5, …, 33. Arched edge weight values ...

A novel performance metric for grey-scale edge detection

Williams, Ian
Svoboda, D.
Bowring, N.

January 2010

This paper will discuss grey-scale edge detection evaluation techniques. It will introduce three of ...

Comparison of edge detection by RFGL and RCFGL in real data.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

The y axis corresponds to the proportion of edges in seven mutually exclusive categories out of all ...

Average errors of edge length (a) and surface area (b) by different measurement methods.

Tamara Dogandžić (5637182)
David R. Braun (258054)
Shannon P. McPherron (764553)

September 2015

Average errors of edge length (a) and surface area (b) by different measurement methods.</p

Comparing edge detection techniques.

Katrina K. Treloar (425532)
Matthew J. Simpson (425533)

June 2013

Comparing three edge detection techniques for barrier assays with two different cell densities: 1...

Inferred vs. simulated weights for three simulated observers.

Ana Radonjić (6585683)
Nicolas P. Cottaris (6585686)
David H. Brainard (349665)

April 2019

The simulated observer color-material weights are shown in green (identical to those shown for corre...

Comparative evaluation of three algorithms in overall orientation of the synthetic phenotype network.

Huange Wang (619576)
Fred A. van Eeuwijk (358696)

August 2014

Sample size, means and standard deviations of the proportion of true positive edges that were cor...

Comparison of edge-weight estimation performance for simulations with three conditions.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

Top and bottom rows respectively correspond to the SSE of methods in scenario (S1) and scenario (S2)...

Comparison of edge-weight estimation performance for simulations studying effect of ordering.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

Top row corresponds to scenario (S5) which has three conditions, and the next two rows correspond to...

Comparison of edge detection performance for simulations with three conditions.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

Top and bottom rows respectively correspond to the precision-recall curves in scenario (S1) and scen...

Performance comparison for simulation with 3 conditions.

Yafei Lyu (4544320)
Lingzhou Xue (3617093)
Feipeng Zhang (4498429)
Hillary Koch (5778071)
Laura Saba (74165)
Katerina Kechris (436022)
Qunhua Li (484957)

October 2018

Top row (A-D): ROC curve for edge detection for the settings of S1-S4; Bottom row (E-H): SSE for edg...

Comparison of edge detection performance for simulations with four conditions.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

Top and bottom rows respectively correspond to the ROC curves in scenario (S3) and scenario (S4). Th...

Comparison of run-time for simulations with three and four conditions.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

Top row corresponds to the run-times in seconds of different methods in scenario (S1) and scenario (...

Comparison of edge-preserving performance on a natural image.

Xueshun Pang (5665183)
Suqi Zhang (797690)
Junhua Gu (797691)
Lingling Li (427154)
Boying Liu (797692)
Huaibin Wang (797693)

September 2015

(a) The natural image, results by (b) LGM (λ = 0.35), and (c) ILGM(λ = 0.0035). (d)...

Edge Weight Distributions.

Matthew Burgess (2802568)
Eytan Adar (6156)
Michael Cafarella (2802571)

May 2016

Histogram of edge weights on a benchmark graph with μ = 0.4 and 20% of the edges removed: ...

Edge weight calculations, for the arched and slanted streamline paths of Fig 4, as a function of seed point density.

Luis M. Colon-Perez (769593)
Caitlin Spindler (769594)
Shelby Goicochea (769595)
William Triplett (769596)
Mansi Parekh (769597)
Eric Montie (238233)
Paul R. Carney (131055)
Catherine Price (769598)
Thomas H. Mareci (481562)

July 2015

The seed point density is P = n3, where n = 1, 3, 5, …, 33. Arched edge weight values ...

A novel performance metric for grey-scale edge detection

Williams, Ian
Svoboda, D.
Bowring, N.

January 2010

This paper will discuss grey-scale edge detection evaluation techniques. It will introduce three of ...

Comparison of edge detection by RFGL and RCFGL in real data.

Souvik Seal (12437166)
Qunhua Li (484957)
Elle Butler Basner (14341204)
Laura M. Saba (9437533)
Katerina Kechris (436022)

January 2023

The y axis corresponds to the proportion of edges in seven mutually exclusive categories out of all ...

Average errors of edge length (a) and surface area (b) by different measurement methods.

Tamara Dogandžić (5637182)
David R. Braun (258054)
Shannon P. McPherron (764553)

September 2015

Average errors of edge length (a) and surface area (b) by different measurement methods.</p

Comparing edge detection techniques.

Katrina K. Treloar (425532)
Matthew J. Simpson (425533)

June 2013

Comparing three edge detection techniques for barrier assays with two different cell densities: 1...

Inferred vs. simulated weights for three simulated observers.

Ana Radonjić (6585683)
Nicolas P. Cottaris (6585686)
David H. Brainard (349665)

April 2019

The simulated observer color-material weights are shown in green (identical to those shown for corre...

Comparative evaluation of three algorithms in overall orientation of the synthetic phenotype network.

Huange Wang (619576)
Fred A. van Eeuwijk (358696)

August 2014

Sample size, means and standard deviations of the proportion of true positive edges that were cor...

Comparison of edge-weight estimation performance for simulations with three conditions.

Abstract

Extracted data

Comparison of edge-weight estimation performance for simulations with three conditions.

Abstract

Extracted data

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