Center-Based iPSC Colony Counting with Multi-Task Learning

Sami, Mirza Tanzim; Yan, Da; Joy, Bhadhan Roy; Khalil, Jalal; Cevallos, Ricardo R.; Hossain, Md Emon; Hu, Kejin; Zhou, Yang

doi:10.1109/icdm54844.2022.00150

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2023

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Cited by 2 publications

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“…Unfortunately, there are no structured dataset about rice leaf disease. Some researchers perform some classification task with a very few numbers of data with white background and it is also possible couting different types of diseases [1][2]. But the most important thing is the presented dataset contain white background image as well as field background image.…”

Section: Data Descriptionmentioning

confidence: 99%

Dhan-Shomadhan: A Dataset of Rice Leaf Disease Classification for Bangladeshi Local Rice

Hossain¹,

Abujar²,

Noori³

et al. 2021

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This dataset represents almost all the harmful diseases for rice in Bangladesh. This dataset consists of 1106 image of five harmful diseases called Brown Spot, Leaf Scaled, Rice Blast, Rice Turngo, Steath Blight in two different background variation named field background picture and white background picture. Two different background variation helps the dataset to perform more accurately so that the user can use this data for field use as well as white background for decision making. The data is collected from rice field of Dhaka Division. This dataset can use for rice leaf diseases classification, diseases detection using Computer Vision and Pattern Recognition for different rice leaf disease.

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Section: Data Descriptionmentioning

confidence: 99%