This dataset describes a collection of 700 different leaders throughout European history across 22 different states. Each leader is described by eight different categories of information: first name, last name/title, the century they ruled, the state in which they ruled, their formal position, their dynasty/family/political party, cause of death, and years of reign. This information can be used for training neural networks targeted at high level associative learning. 

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BTH Trucks in Aerial Images Dataset contains videos of 17 flights across two industrial harbors' parking spaces over two years.

Instructions: 

If you use these provided data in a publication or a scientific paper, please cite the dataset accordingly.

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With the rapid development of augmented reality

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With the rapid development of augmented reality

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This dataset contains 4669820 ratings from 1499238 users to 351109 movies on the imdb.com website. This data is collected from reviews (https://www.imdb.com/review/rw0000001/). Each row in this dataset is as follows:

userID, movieID, rating, review date

For example : 

ur18238764, tt2177461, 9, 22 January 2019

Instructions: 

Use the following code to read the dataset :

import numpy as np

dataset = np.load ("Dataset.npy")

print (dataset [0])

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Instructions: 

This repository contains:

  • age-stratified Covid-19 case and fatality data for different countries and at different points in time, and
  • an interactive Jupyter notebook for mediation analysis of age-related causal effects on case fatality rates,

published as part of the following paper:

"Simpson's paradox in Covid-19 case fatality rates: a mediation analysis of age-related causal effects". J von Kügelgen*, L Gresele*, B Schölkopf. (*equal contribution). https://arxiv.org/abs/2005.07180

We provide the following three separate datasets:

  • a dataset containing only the most recent numbers from: Argentina, China, Colombia, Italy, Netherlands, Portugal, South Africa, Spain, Sweden, Switzerland, South Korea and the Diamond Princess cruise ship (last checked: end of May 2020)
  • a longitudinal dataset containing several reports from Italy (9 March - 26 May 2020)
  • a longitudinal dataset containing several reports from Spain (22 March - 29 May 2020)

All numbers of confirmed cases and fatalities are stratified by age into groups of 10 years (0-9, 10-19, 20-29, 30-39, 40-49, 50-59, 60-69, 70-79, 80+), and contain the date and country of reporting, as well as links to the corresponding sources (generally health agenices/ministries, or scientific publications).

Please consult the paper and notebook for further details.

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This paper produces a data set containing 1127 images, using VOC12 format, the size of the image is 3840*2160, and the corresponding relation of file names

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Semantic segmentation is the topic of interest among deep learning researchers in the recent era.  It has many applications in different domains including, food recognition. In the case of food recognition, it removes the non-food background from the food portion. There is no large public food dataset available to train semantic segmentation models. We prepared a dataset named ’SEG-FOOD’[44] containing images of FOOD101, PFID, and Pakistani Food dataset and open-sourced the annotated dataset for future research. We annotated the images using JS Segment annotator.

Instructions: 

*  For detailed experimentation, please refer to our paper which is under review. we will update the link of that later.

* For starter code please refer to our Github repository. https://github.com/ghalib2021/SEGFOOD

* Note: This dataset contains images from Food101, PFID, and Pakistani Food Dataset. Our main contribution is the manual annotation of the food images for background removal using semantic segmentation and collection of Pakistani food dataset images. Please cite our work besides the original dataset collector if you are using a segmented dataset otherwise, cite the original dataset collector.

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