ImageNet-Sketch data set consists of 50,889 images, approximately 50 images for each of the 1000 ImageNet classes. The data set is constructed with Google Image queries "sketch of ", where is the standard class name. Only within the "black and white" color scheme is searched. 100 images are initially queried for every class, and the pulled images are cleaned by deleting the irrelevant images and images that are for similar but different classes. For some classes, there are less than 50 images after manually cleaning, and then the data set is augmented by flipping and rotating the images.

SketchyCOCO dataset consists of two parts:

Object-level data

Object-level data contains $20198(train18869+val1329)$ triplets of {foreground sketch, foreground image, foreground edge map} examples covering 14 classes, $27683(train22171+val5512)$ pairs of {background sketch, background image} examples covering 3 classes.

Scene-level data

Scene-level data contains $14081(train 11265 + val 2816)$ pairs of {foreground image&background sketch, scene image} examples, $14081(train 11265 + val 2816)$ pairs of {scene sketch, scene image} examples and the segmentation ground truth for $14081(train 11265 + val 2816)$ scene sketches. Some val scene images come from the train images of the COCO-Stuff dataset for increasing the number of the val images of the SketchyCOCO dataset.

These environmental raster covariate, geospatial vector data, and tabular data were compiled as input data for the Automated Reference Toolset (ART) algorithm.

Geological sketch on heavy paper, with annotation in pencil and ink, rich in detail, in fair condition. Observation measure: observations only. Map size: B2. Keywords: AUCKLAND ISLANDS; GEOLOGIC MAPS; MUSGRAVE INLET

This study involved human participant data from the Department of Horticulture and Landscape Architecture. To protect the privacy of the individuals, all de-identified MRI-scanned raw data files are available to view and download.

Provide information on drawing sets for all the buildings nationwide, as well as the documents relating to the Building Modification Request system.

DOT Art collaborates with community-based organizations to commission artists to design and install temporary art on DOT property.

The objective of this SHREC'12 track is to evaluate the performance of different sketch-based 3D model retrieval algorithms using both hand-drawn and standard line drawings sketch queries on a watertight 3D model dataset. Sketch-based 3D model retrieval is to retrieve 3D models using a 2D sketch as input. This scheme is intuitive and convenient for users to search for relevant 3D models and also important for several applications including sketch-based modeling and sketch-based shape recognition. However, most existing 3D model retrieval algorithms target the Query-by-Model framework, that is, using existing 3D models as queries. Much less research work has been done regarding the Query-by-Sketch framework. In addition, until now there was no comprehensive evaluation or comparison for available sketch-based retrieval algorithms. Considering of this, we organized this track to foster this challenging research area by providing a common sketch-based retrieval benchmark and soliciting retrieval results from current state-of-the-art retrieval methods for comparison. We also provide corresponding evaluation code for computing a set of performance metrics similar to those used in the Query-by-Model retrieval technique. Dataset: 3D target Models is 400, 2D query set comprises two subsets: (1) Hand-drawn sketches, and (2) Standard line drawings Please cite the paper: [1] B. Li, T. Schreck, A. Godil, M. Alexa, T. Boubekeur, B. Bustos, J. Chen, M. Eitz, T. Furuya, K. Hildebrand, S. Huang, H. Johan, A. Kuijper, R. Ohbuchi, R. Richter, J. M. Saavedra, M. Scherer, T. Yanagimachi, G. J. Yoon, S. M. Yoon, In: M. Spagnuolo, M. Bronstein, A. Bronstein, and A. Ferreira (eds.), SHREC'12 Track: Sketch-Based 3D Shape Retrieval, Eurographics Workshop on 3D Object Retrieval 2012 (3DOR 2012), 2012.

Jackson Pollock’s abstract poured paintings are celebrated for their striking aesthetic qualities. They are also among the most financially valued and imitated artworks, making them vulnerable to high-profile controversies involving Pollock-like paintings of unknown origin. Given the increased employment of artificial intelligence applications across society, we investigate whether established machine learning techniques can be adopted by the art world to help detect imitation Pollocks. The low number of images compared to typical artificial intelligence projects presents a potential limitation for art-related applications. To address this limitation, we develop a machine learning strategy involving a novel image ingestion method which decomposes the images into sets of multi-scaled tiles. Leveraging the power of transfer learning, this approach distinguishes between authentic and imitation poured artworks with an accuracy of 98.9%. The machine also uses the multi-scaled tiles to genera..., The images of the 588 artworks used in our study were acquired in collaboration with The Pollock-Krasner Foundation, The Pollock-Krasner Study Center, The International Foundation for Art Research, and Francis V. O’Connor (chief Pollock connoisseur and co-author of the Catalogue Raissonne). The collection and analysis method of all images complies with the terms and conditions for the sources of the data. The S1 Table provides a comprehensive list of the image sets. The image sets feature 2 overall categories of artwork - those established as being created by Pollock and those established to be by other artists., , # Art Images

https://doi.org/10.5061/dryad.m905qfv91

This data contains all the individual tiles of the art images used for the paper "Using Machine Learning to Distinguish Between Authentic and Imitation Jackson Pollock Poured Paintings: A Tile-Driven Approach to Computer Vision"

Description of the data and file structure

Each art image is cropped and then tiled at multiple physical size scales. Each zipped folder contains all the tiles for all the images at a particular size scale (e.g. folder "20" refers to a 20cm x 20cm square tile). The range of tile sizes is from 10cm to 360cm every 5cm and "Max". Â

Due to the dryad storage limitations the "10" folder was split into several zipped folders, "10_ACDEF", "10_G", "10_J", and "10_P" .Â

They should be combined into one single folder labeled "10".

The final folder structure should be as follows

"ImageClassifier/Paintings/Processed/Raw/ (all tile size folders)"

When running code no...

Graph Drawing Program Using Search Based TechniquesThis package contains the source code of a Java program which includes the algorithms of 4 search based techniques (hill climbing, simulated annealing, tabu search, and path relinking) used to draw general graph layouts with undirected straight edges. The program includes a GUI which allows the user to adjust the parameters for each method according to user's preferences.GraphDrawing.zipData SetsThis package includes all the datasets used in our paper submitted to Plos One. Each data file starts with a number, N, which represents the number of test cases in the file, followed by N test cases. Each test case starts with a number V, which represents the number of nodes in the graph, followed by V lines, each line represents the adjacency list of each node.DataSets.zip

Additional file 3: Table S2. The list of the species-taxid and best-match-species-taxid of the impurity genomes.

1680 Global exporters importers export import shipment records of Fine wire drawing machine with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

China Art & Craft: Profit from Sales Revenue: Year to Date data was reported at 84.235 RMB bn in Oct 2015. This records an increase from the previous number of 74.398 RMB bn for Sep 2015. China Art & Craft: Profit from Sales Revenue: Year to Date data is updated monthly, averaging 28.263 RMB bn from Dec 1998 (Median) to Oct 2015, with 88 observations. The data reached an all-time high of 103.228 RMB bn in Dec 2014 and a record low of 2.935 RMB bn in Feb 2007. China Art & Craft: Profit from Sales Revenue: Year to Date data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Industrial Sector – Table CN.BIH: Cultural, Educational, Art, Craft, Sport and Recreational Product: Art and Craft.

37 Global import shipment records of Art Board with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Sketches from a hunter's album is a book. It was written by Ivan Sergeevich Turgenev and published by Penguin in 1967.

Temporary art exhibitions and installations in New York City Department of Parks & Recreation properties since 2000. To convert the JSON feed to CSV (or excel), use: https://json-csv.com/ Data Dictionary: https://docs.google.com/spreadsheets/d/1tDKjYnYG1xPkMhBPr8vPKWVSoEhSBxYWkXsCDkgpBcE/edit?usp=sharing

Experiential art refers to installations or exhibitions aiming to deliver an immersive experience to the audience by relying on a range of new media, such as projections, videos, VR, or AR technologies. Between June 2018 and May 2019, two immersive art spaces opened in Tokyo, teamLab Borderless and teamLab Planets which recorded a combined attendance of roughly 3.55 million. Over that period, the two venues hosting the digital works created by the Japan-based art collective teamLab recorded around 69 million and 37.5 million U.S. dollars in gross sales, respectively.

6817 Global import shipment records of Drawing Board with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

5343 Global export shipment records of Drawing Ruler with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

This layer has been deprecated and archived. Data are updated in a new layer Tempe Public Art (open data) starting in April 2023 at https://data.tempe.gov/datasets/tempegov::tempe-public-art-open-data/about.Content provided in this feature is presented as points. These points help visualize the locations of Tempe's diverse collection of permanent and temporary public art. Tempe Public Art promotes artistic expression, bringing people together to strengthen Tempe's sense of community and place. Data Dictionary