Artificial Intelligence

The orchid flower dataset was selected from the northern part of Thailand. The dataset contains Thai native orchid flowers, and each class contains at least 20 samples. The orchid dataset including 52 species and the visual characteristics of the flower are varying in terms of shape, color, texture, size, and the other parts of the orchid plant like a leaf, inflorescence, roots, and surroundings. All images are taken from many devices such as a digital camera, a mobile phone, and other equipment. The orchids dataset contains 3,559 images from 52 categories.

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  • Artificial Intelligence
  • Last Updated On: 
    Thu, 01/02/2020 - 23:16

    This is a dataset consisting of 8 features extracted from 70,000 monochromatic still images adapted from the Genome Project Standford's database, that are labeled in two classes: LSB steganography (1) and without LSB Steganography (0). These features are Kurtosis, Skewness, Standard Deviation, Range, Median, Geometric Mean, Hjorth Mobility, and Hjorth Complexity, all extracted from the histograms of the still images, including random spatial transformations. The steganographic function embeds five types of payloads, from 0.1 to 0.5.

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  • Artificial Intelligence
  • Last Updated On: 
    Thu, 11/21/2019 - 20:14

    Features Extracted from BraTS 2012-2013

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  • Artificial Intelligence
  • Last Updated On: 
    Thu, 11/21/2019 - 12:55

    We provide a large benchmark dataset consisting of about: 3.5 million keystroke events; 57.1 million data-points for accelerometer and gyroscope each; and 1.7 million data-points for swipes. Data was collected between April 2017 and June 2017 after the required IRB approval. Data from 117 participants, in a session lasting between 2 to 2.5 hours each, performing multiple activities such as: typing (free and fixed text), gait (walking, upstairs and downstairs) and swiping activities while using desktop, phone and tablet is shared. 

     

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  • Artificial Intelligence
  • Last Updated On: 
    Thu, 01/02/2020 - 00:15

    This package contains 942 synthetic event streams that simulate concept drift in business processes. Each stream has only one drift. Different stream sizes, types and perspective of drift, and noise percentual are applied. Each event in the stream contains four main attributes: case identification, event name, event start time, event completion time.

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  • Artificial Intelligence
  • Last Updated On: 
    Tue, 11/19/2019 - 09:30

    An accurate analysis of fluid–structure interaction (FSI) at compliant arteries via ultrasound (US) imaging and numerical modeling is a limitation of several studies. In this study, we propose a deep learning-based boundary detection and compensation (DL-BDC) technique that can segment vessel boundaries by harnessing the convolutional neural network and wall motion compensation in near-wall flow dynamics. The segmentation performance of the technique is evaluated through numerical simulations with synthetic US images and in vitro experiments.

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  • Artificial Intelligence
  • Last Updated On: 
    Fri, 11/08/2019 - 11:13

    An accurate and reliable image-based quantification system for blueberries may be useful for the automation of harvest management. It may also serve as the basis for controlling robotic harvesting systems. Quantification of blueberries from images is a challenging task due to occlusions, differences in size, illumination conditions and the irregular amount of blueberries that can be present in an image. This paper proposes the quantification per image and per batch of blueberries in the wild, using high definition images captured using a mobile device.

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  • Artificial Intelligence
  • Last Updated On: 
    Thu, 01/02/2020 - 09:36

    This dataset contains in-silico results of insulin treatment using a fully automated artificial pancreas algorithm based on reinforcement learning for FDA-approved virtual patients (C. D. Man et al., 2014) with type 1 diabetes (10 adults and 10 adolescents). 

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  • Artificial Intelligence
  • Last Updated On: 
    Mon, 11/04/2019 - 03:07

    eye recognition dataset

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  • Artificial Intelligence
  • Last Updated On: 
    Sun, 11/03/2019 - 07:53

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  • Artificial Intelligence
  • Last Updated On: 
    Fri, 11/01/2019 - 02:53

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