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GenWiki: A Dataset of 1.3 Million Content-Sharing Text and Graphs for Unsupervised Graph-to-Text Generation
Jan 2, 2024
Jin, Zhijing, 2024, "GenWiki: A Dataset of 1.3 Million Content-Sharing Text and Graphs for Unsupervised Graph-to-Text Generation", https://doi.org/10.17617/3.YGO7EW, Edmond, V1
Paper: "GenWiki: A Dataset of 1.3 Million Content-Sharing Text and Graphs for Unsupervised Graph-to-Text Generation" (COLING 2020) by Zhijing Jin, Qipeng Guo, Xipeng Qiu, and Zheng Zhang. (https://aclanthology.org/2020.coling-main.217/) Abstract: Data collection for the knowledge graph-to-text generation is expensive. As a result, research on unsup...
Supplementary Material for "Performance Review of Retraining and Transfer Learning of DeLTA 2.0 for Image Segmentation for Pseudomonas fluorescens SBW25"
Supplementary Material for "Performance Review of Retraining and Transfer Learning of DeLTA 2.0 for Image Segmentation for Pseudomonas fluorescens SBW25"
Dec 18, 2023
Fortmann-Grote, Carsten; Gericke, Beate Constanze; Werth, Sören; Degner, Finn; Hüttmann, Tom, 2023, "Supplementary Material for "Performance Review of Retraining and Transfer Learning of DeLTA 2.0 for Image Segmentation for Pseudomonas fluorescens SBW25"", https://doi.org/10.17617/3.MCK0KK, Edmond, V1
This upload contains all raw data, trained tensorflow models, and python code used for training and validation of deep learning image segmentation as described in the forthcoming paper "Performance Review of Retraining and Transfer Learning of DeLTA 2.0 for Image Segmentation for Pseudomonas fluorescens SBW25"
User Study Dataset for Understanding On-Site Construction Activities with Haptic Perception
User Study Dataset for Understanding On-Site Construction Activities with Haptic Perception
Nov 5, 2023
Gong, Yijie; Javot, Bernard; Lauer, Anja Patricia Regina; Sawodny, Oliver; Kuchenbecker, Katherine J., 2023, "User Study Dataset for Understanding On-Site Construction Activities with Haptic Perception", https://doi.org/10.17617/3.PAFGCA, Edmond, V1
We encourage viewers to select the "Tree" view, rather than "Table" view, in order to see the files organized by their respective folders. The dataset includes the following: 1. A readme file explaining our user study and the data, 2. Raw acceleration data, 3. Raw robot data, 4. Questionnaire responses, 5. Consent form, 6. Robot motion videos. This...
Analysis scripts and raw data for Cookiewall measurements
Oct 23, 2023
Rasaii, Seyedali, 2023, "Analysis scripts and raw data for Cookiewall measurements", https://doi.org/10.17617/3.TREBZR, Edmond, V1
This collection contains analysis scripts and raw data to reproduce our analysis for the web cookie measurements to investigate cookiewalls in the wild. The results are published in the paper "Thou Shalt Not Reject: Analyzing Accept-Or-Pay Cookie Banners on the Web" published at the "ACM Internet Measurement Conference 2023" (IMC 2023). More inform...
Supplementary material: Machine learning based classification of vector field configurations
Sep 29, 2023
Pathak, Swapneel Amit; Holt, Sam; Lang, Martin; Fangohr, Hans, 2023, "Supplementary material: Machine learning based classification of vector field configurations", https://doi.org/10.17617/3.KG33A1, Edmond, V1
The data set contains the supplementary material to support the paper: Machine learning based classification of vector field configurations. The dataset contains simulation files, scripts for data generation and a notebook which shows the steps undertaken to perform the study. The study shows how to cluster magnetisation vector fields into meaningf...
Supplementary material: Vision for Unified Micromagnetic Modeling (UMM) with Ubermag
Sep 29, 2023
Fangohr, Hans; Lang, Martin; Holt, Samuel J. R.; Pathak, Swapneel Amit; Zulfiqar, Kauser; Beg, Marijan, 2023, "Supplementary material: Vision for Unified Micromagnetic Modeling (UMM) with Ubermag", https://doi.org/10.17617/3.D5FT5Y, Edmond, V1
Supplementary material for the "Vision for Unified Micromagnetic Modeling (UMM) with Ubermag" paper containing the source code and software requirements.
A Real-World Metal-Layer SEM Image Dataset with Partial Labels
Sep 26, 2023
Rothaug, Nils; Klix, Simon; Auth, Nicole; Böcker, Sinan; Puschner, Endres; Becker, Steffen; Paar, Christof, 2023, "A Real-World Metal-Layer SEM Image Dataset with Partial Labels", https://doi.org/10.17617/3.HY5SYN, Edmond, V1
This dataset contains scanning electron microscope (SEM) images and labels from our paper "Towards Unsupervised SEM Image Segmentation for IC Layout Extraction", which are licensed under a Creative Commons Attribution 4.0 International License (CC-BY 4.0). The SEM images cover the logic area of the metal-1 (M1) and metal-2 (M2) layers of a commerci...
Drosophila Brain Model
Sep 21, 2023
Shiu, Philip; Spiller, Nico, 2023, "Drosophila Brain Model", https://doi.org/10.17617/3.CZODIW, Edmond, V3
A computational model of the Drosophila brain (bioRxiv, Github)
Cityscapes Parts
Aug 28, 2023
Losch, Max Maria, 2023, "Cityscapes Parts", https://doi.org/10.17617/3.B1IZS6, Edmond, V1
For 100 Cityscapes images, this dataset provides additional annotation of 40 subordinate concepts belonging to the original 19 classes. This dataset requires the original Cityscapes dataset which can be found at: https://www.cityscapes-dataset.com
Photomanipulation of minimal synthetic cells: area increase, softening and interleaflet coupling of membrane models doped with azobenzene-lipid photoswitches
Photomanipulation of minimal synthetic cells: area increase, softening and interleaflet coupling of membrane models doped with azobenzene-lipid photoswitches
Aug 25, 2023
Dimova, Rumiana, 2023, "Photomanipulation of minimal synthetic cells: area increase, softening and interleaflet coupling of membrane models doped with azobenzene-lipid photoswitches", https://doi.org/10.17617/3.CWOZQO, Edmond, V1
Supporting data (simulation files, movies) for Aleksanyan et al. (2023) Advanced Science
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