1 representing a healthy plant and5aseverely diseased plant. For each category of disease, we thus have other sub-classes that represent how severe the disease is. This paper extends previous work in this field and introduces the determination of the severity of disease from leaf images of diseased cassava plants using machine learning techniques.

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Group Rules The Encyclopedia of Life project (EOL, ) is building an open access collection of biodiversity information. By donating your photos of plants, animals, fungi, and microbes to this group, you are joining a global community of scientists and nature enthusiasts with a mission to document and analyze the splendor of life on earth.

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Abstract: This dataset consists in a collection of shape and texture features extracted from digital images of leaf specimens originating from a total of 40 different plant species. This dataset was created by Pedro F. B. Silva and André R. S. Marçal using leaf specimens collected by Rubim ...

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This spider plant is the 2nd generation of a small spiderling "liberated" from a sickly plant under bad (mercury vapor?) shop/gym lighting. Again, the 'Big Brother' of this one is at J.R.'s house trying to make the windowsill disappear.

An essential website is the USDA Natural Resources Conservation Service Plants Database.. This huge database includes a search function utilizing a common name or scientific name, photos and illustrations, geographic distribution maps, and links to other resources with even more information about a specific plant.

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This study reports a machine vision system for the identification of the visual symptoms of plant diseases, from coloured images. Diseased regions shown in digital pictures of cotton crops were enhanced, segmented, and a set of features were extracted from each of them.

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List of datasets for machine learning research. Jump to navigation Jump to search ... Datasets consisting primarily of images or videos for tasks such as object detection, ... 12 category dataset of plant seedlings. Labelled images, segmented images, 5544 Images Classification, detection 2017

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Machine identification of buds in images of plant shoots Kalman Peleg~ Oded Cohen~ Meira Ziv~ and Eitan Kimmel Department of Agricultural Engineering, Technion Israel Institute of Technology, Haifa 32000, Israel

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