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15,761 to 15,770 of 16,786 Results

variance-400.tab Sep 27, 2022 - Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters" Tabular Data - 40.4 KB - 6 Variables, 450 Observations - UNF:6:9HyN/2jlcVdPuuq52hIwpQ== This file contains a synthetic dataset. It has five numeric dimensions. The data records of this dataset describe three classes also forming clusters in all dimensions. This dataset has 400 records.
variance-800.tab Sep 27, 2022 - Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters" Tabular Data - 76.4 KB - 6 Variables, 850 Observations - UNF:6:dHHpAC3qiIpFizO+EWIYiA== This file contains a synthetic dataset. It has five numeric dimensions. The data records of this dataset describe three classes also forming clusters in all dimensions. This dataset has 800 records.
KonIQ-10k IQA Database Sep 23, 2022 - SFB-TRR 161 A05 "Image/Video Quality Assessment: From Test Databases to Similarity-Aware and Perceptual Dynamic Metrics" Hosu, Vlad; Lin, Hanhe; Szirányi, Tamas; Saupe, Dietmar, 2022, "KonIQ-10k IQA Database", https://doi.org/10.18419/DARUS-2435, DaRUS, V1, UNF:6:2Pw1H0RwWd4G4kLDsT/bjA== [fileUNF] KonIQ-10k is, at the time of publication, the largest IQA dataset to date consisting of 10,073 quality scored images. This is the first in-the-wild database aiming for ecological validity, with regard to the authenticity of distortions, the diversity of content, and quality-related indicators. Through the use of crowdsourcing, we obtained 1.2 milli...
koniq10k_1024x768.zip Sep 23, 2022 - KonIQ-10k IQA Database ZIP Archive - 5.2 GB - MD5: 85f076d7a43b2e306f7080814f69af3e
koniq10k_512x384.zip Sep 23, 2022 - KonIQ-10k IQA Database ZIP Archive - 731.4 MB - MD5: dc213332574e8431a86c7ff34e1fa924
koniq10k_indicators.tab Sep 23, 2022 - KonIQ-10k IQA Database Tabular Data - 838.4 KB - 9 Variables, 10073 Observations - UNF:6:R0ufUtMNYygvRLURoMlQJQ==
koniq10k_scores_and_distributions.tab Sep 23, 2022 - KonIQ-10k IQA Database Tabular Data - 812.3 KB - 10 Variables, 10073 Observations - UNF:6:S4OuGLN8dEvJ6S0Sr8AGdA==
Supplemental Material for Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution Sep 21, 2022 - SFB-TRR 161 B01 "Adaptive Self-Consistent Visualization" Rodrigues, Nils; Schulz, Christoph; Döring, Sören; Baumgartner, Daniel; Krake, Tim; Weiskopf, Daniel, 2022, "Supplemental Material for Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution", https://doi.org/10.18419/DARUS-3055, DaRUS, V1 Supplemental material for the paper "Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution". Contains: math behind Relaxed Dot Plots additional images pseudo-anonymous study data source code for library and test application To view the material, extract supplemental.zip and open index.html in a web browser.
supplemental.zip Sep 21, 2022 - Supplemental Material for Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution ZIP Archive - 169.9 MB - MD5: 3d83b74d9c8f3607dc0db81aed8eaf82
0001_initial.py Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering" Python Source Code - 856 B - MD5: b1c32aa0e87023345dede5b9f3d67e98

variance-400.tab

Sep 27, 2022 - Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"

Tabular Data - 40.4 KB - 6 Variables, 450 Observations -

This file contains a synthetic dataset. It has five numeric dimensions. The data records of this dataset describe three classes also forming clusters in all dimensions. This dataset has 400 records.

variance-800.tab

Sep 27, 2022 - Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"

Tabular Data - 76.4 KB - 6 Variables, 850 Observations -

This file contains a synthetic dataset. It has five numeric dimensions. The data records of this dataset describe three classes also forming clusters in all dimensions. This dataset has 800 records.

KonIQ-10k IQA Database

Sep 23, 2022 - SFB-TRR 161 A05 "Image/Video Quality Assessment: From Test Databases to Similarity-Aware and Perceptual Dynamic Metrics"

Hosu, Vlad; Lin, Hanhe; Szirányi, Tamas; Saupe, Dietmar, 2022, "KonIQ-10k IQA Database", https://doi.org/10.18419/DARUS-2435, DaRUS, V1, UNF:6:2Pw1H0RwWd4G4kLDsT/bjA== [fileUNF]

KonIQ-10k is, at the time of publication, the largest IQA dataset to date consisting of 10,073 quality scored images. This is the first in-the-wild database aiming for ecological validity, with regard to the authenticity of distortions, the diversity of content, and quality-related indicators. Through the use of crowdsourcing, we obtained 1.2 milli...

koniq10k_1024x768.zip

Sep 23, 2022 - KonIQ-10k IQA Database

ZIP Archive - 5.2 GB -

koniq10k_512x384.zip

Sep 23, 2022 - KonIQ-10k IQA Database

ZIP Archive - 731.4 MB -

koniq10k_indicators.tab

Sep 23, 2022 - KonIQ-10k IQA Database

Tabular Data - 838.4 KB - 9 Variables, 10073 Observations -

koniq10k_scores_and_distributions.tab

Sep 23, 2022 - KonIQ-10k IQA Database

Tabular Data - 812.3 KB - 10 Variables, 10073 Observations -

Supplemental Material for Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution

Sep 21, 2022 - SFB-TRR 161 B01 "Adaptive Self-Consistent Visualization"

Rodrigues, Nils; Schulz, Christoph; Döring, Sören; Baumgartner, Daniel; Krake, Tim; Weiskopf, Daniel, 2022, "Supplemental Material for Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution", https://doi.org/10.18419/DARUS-3055, DaRUS, V1

Supplemental material for the paper "Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution". Contains: math behind Relaxed Dot Plots additional images pseudo-anonymous study data source code for library and test application To view the material, extract supplemental.zip and open index.html in a web browser.

supplemental.zip

Sep 21, 2022 - Supplemental Material for Relaxed Dot Plots: Faithful Visualization of Samples and Their Distribution

ZIP Archive - 169.9 MB -

0001_initial.py

Sep 13, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"

Python Source Code - 856 B -

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