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Search results for: AUTOMATIC MUSIC CLASSIFICATION
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SYNAT Music Genre Parameters PCA 19
Open Research DataThe dataset contains feature vector after Principal Component Analysis (PCA) performing, so there are 11 music genres and 19-element vector derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier research studies carried out by the team of authors [1-6]. A collection of 52532 music excerpts described...
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SYNAT_PCA_48
Open Research DataThere is a series of datasets containing feature vectors derived from music tracks. The dataset contains 51582 music tracks (22 music genres) and feature vector after Principal Component Analysis (PCA) performing, so there are 48-element vectors derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier...
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SYNAT_PCA_11
Open Research DataThe dataset contains 51582 music tracks (22 music genres) and feature vector after Principal Component Analysis (PCA) performing, so there are 11-element vectors derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier research studies carried out by the team of authors [1-6]. A collection of more than...
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SYNAT_MUSIC_GENRE_FV_173
Open Research DataThis is the original dataset containing 51582 music tracks (22 music genres) and 173 element-feature vector [1-6,9]. A collection of more than 50000 music excerpts described with a set of descriptors obtained through the analysis of 30-second mp3 recordings was gathered in a database called SYNAT. The SYNAT database was realized by the Gdansk University...
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The aggregation of objects representing buildings in the Kartuzy district - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The aggregation of objects representing Gdańsk district buildings - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The aggregation of objects representing Gdańsk district buildings - scale 1:25000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The aggregation of objects representing buildings in the Kartuzy district - scale 1:25000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The aggregation of objects representing Katowice district buildings - scale 1:25000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The aggregation of objects representing Katowice district buildings - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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LEGO bricks for training classification network
Open Research DataThe data set contains images of 447 different classes of LEGO bricks used for training LEGO bricks classification network. The dataset contains two types of images: photos (10%) and renders (90%) aggregated into respective directories. Each directory (photos and renders) contains 447 directories labeled as the official brick type number. The images...
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EEG data recorded in three mental states
Open Research DataElectroencephalographic (EEG) signals were acquired from 17 (14 males, 3 females) participants aged between 20 and 30 years.
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A study of nighttime vehicle detection algorithms
Open Research DataThis dataset is from my master's thesis "A study of nighttime vehicle detection algorithms". It contains both raw data and preprocessed dataset ready to use. In the pictures below you can see how images were annotated.
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - All accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Bias mitigation benchmark that includes two datasets
Open Research DataISIC-2020 is the largest skin lesion dataset divided into two classes -- benign and malignant. It contains 33126 dermoscopic images from over 2000 patients. The diagnoses were confirmed either by histopathology, expert agreement or longitudinal follow-up. The dataset was gathered by The International Skin Imaging Collaboration (ISIC) from several medical...
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Side-impact accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: Side-impact. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Run off road accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: Run off road. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Elderly people accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: elderly people (65+) - drivers, passengers and . vulnerable road user. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Cyclist accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Cyclists. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Night accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, time of accidents: Night. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Excessive speed accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, cause of accidents: Excessive speed accidents. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Child accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: children - drivers, passengers and . vulnerable road user.. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Alcohol and drug accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Offenders under influence of alcohol or drug - driver or pedestrian. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Pedestrian accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: Pedestrians. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Young drivers accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: young driver offender. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Motorcycle and moped accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, risk group: motorcyclists and mopeds. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Head-on accidents
Open Research DataData contain risk classification on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019, type of accidents: head-on. Measures used to assess the level of risk are (5 classes low, low to medium, medium, medium to high, high):
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High-resolution wind wave parameters in the area of the Gulf of Gdańsk during 21 extreme storms
Open Research DataThis dataset contains the results of wind-wave parameter modelling in the area of the Gulf of Gdańsk (Southern Baltic). For the simulations, a high resolution SWAN model was used. The dataset consists of the significant wave height, the direction of the wave approaching the shore and the wave period during 21 historical, extreme storms. The storms were...
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High-resolution wind wave parameters in the area of the Gulf of Gdańsk during 21 extreme storms (GIS dataset)
Open Research DataThis GIS dataset contains the results of wind-wave parameter modelling in the area of the Gulf of Gdańsk (Southern Baltic). For the simulations, a high resolution SWAN model was used. The dataset consists of the significant wave height, the direction of the wave approaching the shore and the wave period during 21 historical, extreme storms (rasters)....
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The generalization by simplification operator with the Simplify Building tool of objects representing groups of buildings in Gdańsk district - scale 1:10000. Data from OSM
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the Open Street Map databases (OSM) [1].
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A New Adaptive Method for the Extraction of Steel Design Structures from an Integrated Point Cloud
Open Research DataA new automatic and adaptive algorithm for edge extraction from a random point cloud was developed and presented herein. The proposed algorithm was tested using real measurement data. The developed algorithm is able to realistically reduce the amount of redundant data and correctly extract stable edges representing the geometric structures of a studied...
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Ethylene decomposition on TiO2 - UV and Fluorescence lamp
Open Research DataData contain chromatograms recorded during decomposition of ethylene flowing over TiO2 through the quartz tubular shape reactor. TiO2 was coated onto glass plates with dimension of 2cmx2cm, in total 3 plates were used and placed inside reactor. Reactor was irradiated by UV (Special 'TL'E, Philips) or fluorescent (Lumilux, OSRAM) 3 ring-shaped lamps,...
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The generalization of objects representing groups of buildings in the Kartuzy district by simplification operator with the Simplify Building tool - scale 1:10000. Data from OSM.
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the Open Street Map databases (OSM) [1].
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SkinDepth - synthetic 3D skin lesion database
Open Research DataSkinDepth is the first synthetic 3D skin lesion database. The release of SkinDepth dataset intends to contribute to the development of algorithms for:
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Accidents, victims and risk levels on regional roads in pomorskie voivodeship, 2017-2019 - Medium to High and high road sections
Open Research DataData contain road sections with the highest number of accidents and victims on regional roads (voivodeship roads) in pomorskie voivodeship in 2017-2019. Measures used to assess the level of risk is: minimum 4 accidents or 4 seriously injured or fatalities per one kilometer (5 classes: low, low to medium, medium, medium to high, high):
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The generalization by simplification operator with the Simplify Building tool of objects representing groups of buildings in Gdańsk district - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization of objects representing groups of buildings in the Kartuzy district by simplification operator with the Simplify Building tool - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization by simplification operator with the Simplify Building tool of objects representing groups of buildings in Katowice district - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization by simplification operator with the Simplify Building tool of objects representing groups of buildings in Katowice district - scale 1:25000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization by simplification operator with the Simplify Building tool of objects representing groups of buildings in Gdańsk district - scale 1:25000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization by simplification operator with Sester’s method of objects representing groups of buildings in Gdańsk district - scale 1:10000. Data from OSM
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the Open Street Map databases (OSM) [1].
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The generalization of objects representing groups of buildings in the Kartuzy district by simplification operator with the Simplify Building tool - scale 1:25000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The generalization by simplification operator with Sester’s method of objects representing groups of buildings in Kartuzy district - scale 1:10000. Data from OSM
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the Open Street Map databases (OSM) [1].
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The generalization by simplification operator with Chrobak’s method of objects representing groups of buildings in Gdańsk district - scale 1:10000. Data from OSM
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the Open Street Map databases (OSM) [1].
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The generalization by simplification operator with Chrobak’s method of objects representing groups of buildings in Kartuzy district - scale 1:10000. Data from OSM.
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the Open Street Map databases (OSM) [1].
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The orthogonisation of objects simplified using the Chrobak’s method representing groups of buildings in Gdańsk district - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The orthogonalization of simplified objects representing groups of buildings in Gdańsk district using the Simplify Building tool - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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Objects resulting from the sequential generalization of the buildings group in Gdańsk district - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The orthogonisation of objects simplified using the Sester’s method representing groups of buildings in Gdańsk district - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].
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The orthogonalization of objects simplified using the Chrobak’s method representing groups of buildings in Kartuzy district - scale 1:10000
Open Research DataThe process of automatic generalization is one of the elements of spatial data preparation for the purpose of creating digital cartographic studies. The presented data include a part of the process of generalization of building groups obtained from the national geodesy and cartography resource from BDOT10k (10k topographic database) [1].