Computer Vision
An image dataset including five types of weather conditions (cloudy, sunny, foggy, rainy and snowy) was constructed.
This dataset, called FWID, includes 4000 images for each weather category, leading to a total of 20000 images.
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2000 ViewsAn image dataset including five types of weather conditions (cloudy, sunny, foggy, rainy and snowy) was constructed.
This dataset, called FWID, includes 4000 images for each weather category, leading to a total of 20000 images.
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501 ViewsAn image dataset including five types of weather conditions (cloudy, sunny, foggy, rainy and snowy) was constructed.
This dataset, called FWID, includes 4000 images for each weather category, leading to a total of 20000 images.
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3969 Views
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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2755 Views
Features Extracted from BraTS 2012-2013
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155 Views
This dataset contains the comparison results on the 'Euroc' public dataset of DVIO, VINS-Mono, and ROVIO.
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583 Views
This dataset comes up as a benchmark dataset for machines to automatically recognizing the handwritten assamese digists (numerals) by extracting useful features by analyzing the structure. The Assamese language comprises of a total of 10 digits from 0 to 9. We have collected a total of 516 handwritten digits from 52 native assamese people irrespective of their age (12-86 years), gender, educational background etc. The digits are captured in .jpeg format using a paint mobile application developed by us which automatically saves the images in the internal storage of the mobile.
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1160 Views
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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2553 Views
The Contest: Goals and Organisation
The 2019 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), the Johns Hopkins University (JHU), and the Intelligence Advanced Research Projects Activity (IARPA), aimed to promote research in semantic 3D reconstruction and stereo using machine intelligence and deep learning applied to satellite images.
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23362 Views
Attempts to prevent invasion of marine biofouling on marine vessels are demanding. By developing a system to detect marine fouling on vessels in an early stage of fouling is a viable solution. However, there is a lack of database for fouling images for performing image processing and machine learning algorithm.
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2057 Views