CongNaMul: A Dataset for Advanced Image Processing of Soybean Sprouts
- URL: http://arxiv.org/abs/2308.15690v2
- Date: Thu, 31 Aug 2023 02:21:20 GMT
- Title: CongNaMul: A Dataset for Advanced Image Processing of Soybean Sprouts
- Authors: Byunghyun Ban, Donghun Ryu, Su-won Hwang
- Abstract summary: CongNaMul dataset is curated to facilitate tasks such as image classification, semantic segmentation, decomposition, and measurement of length and weight.
The classification task provides four classes to determine the quality of soybean sprouts: normal, broken, spotted, and broken and spotted.
The dataset is expected to be a valuable resource for a wide range of research and applications in the advanced analysis of images of soybean sprouts.
- Score: 0.26786930391553554
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We present 'CongNaMul', a comprehensive dataset designed for various tasks in
soybean sprouts image analysis. The CongNaMul dataset is curated to facilitate
tasks such as image classification, semantic segmentation, decomposition, and
measurement of length and weight. The classification task provides four classes
to determine the quality of soybean sprouts: normal, broken, spotted, and
broken and spotted, for the development of AI-aided automatic quality
inspection technology. For semantic segmentation, images with varying
complexity, from single sprout images to images with multiple sprouts, along
with human-labelled mask images, are included. The label has 4 different
classes: background, head, body, tail. The dataset also provides images and
masks for the image decomposition task, including two separate sprout images
and their combined form. Lastly, 5 physical features of sprouts (head length,
body length, body thickness, tail length, weight) are provided for image-based
measurement tasks. This dataset is expected to be a valuable resource for a
wide range of research and applications in the advanced analysis of images of
soybean sprouts. Also, we hope that this dataset can assist researchers
studying classification, semantic segmentation, decomposition, and physical
feature measurement in other industrial fields, in evaluating their models. The
dataset is available at the authors' repository. (https://bhban.kr/data)
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