基于卷积神经网络的牛疾病实时检测与解释

N. Shivaanivarsha, Pasupuleti Baskaran Lakshmidevi, J. Josy
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引用次数: 1

摘要

牛乳腺炎、牛肿块性皮肤病、牛乳头状瘤病、光敏症等牛疾病的预测和分析在畜牧业领域是非常需要的。近年来卷积神经网络的发展在许多领域取得了巨大的进步。本研究提出了一种基于卷积神经网络的有效智能移动应用模型,利用tehable machine和TensorFlow Lite对牛乳腺炎、肿块性皮肤病、乳头状瘤病和光敏症等四种重要疾病进行早期识别。检测牛疾病的准确率约为98.58%。这款移动应用程序最终成为养牛农民的最佳合作伙伴,可以快速检测牛疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A ConvNet based Real-time Detection and Interpretation of Bovine Disorders
The prediction and analysis of bovine diseases like, Bovine Mastitis, Lumpy Skin Disease, Papillomatosis, and Photosensitisation in cattle are highly wanted in the field of animal husbandry. The recent time development in ConvNets has made enormous advances in many fields. This study proposes an effective smart mobile application model constructed based on ConvNet, by image classification using Teachable machine and TensorFlow Lite to recognize four important bovine diseases like, Bovine Mastitis, Lumpy Skin Disease, Papillomatosis and Photosensitisation in the early phases of disease development. It detects bovine diseases with an accuracy of about 98.58%. This mobile application ultimately makes the best partner for the farmers in cattle farming, to detect Bovine diseases expeditiously.
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