基于深度学习的畜牧业图像识别

Yan Qi, Cheng Baiyang, Luo Lan
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引用次数: 0

摘要

深度学习技术是新兴科技革命和畜牧业革命的重要新生力量,在中国畜牧业走向数字化、信息化、智慧化的过程中发挥着至关重要的作用。基于深度学习的图像识别在畜牧业中的应用,为养殖业的疾病预防、精准识别和生物安全防控问题提供了新的解决方案,将成为推动畜牧业走向现代化的有力助推器。利用卷积神经网络在提取一个特征后根据特征类型完成链接分类,然后完成数据预处理,并利用基于超像素的图像分割和SIFT算法完成图像分割和图像特征提取,最后通过卷积神经网络和支持向量机完成动物动作的分类和预测。带动畜牧业整体管理水平的提高,成为推动智能化畜牧业发展的有效途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Learning Based Image Recognition In Animal Husbandry
Deep learning technology is an important new force in the emerging science and technology revolution and the revolution of the animal husbandry industry, and plays a crucial role in the process of being digitization, informatization and wisdom of the animal husbandry industry in China. The application of deep learning-based image recognition in the livestock industry provides a new solution to the problems of disease prevention, precise identification and biosafety prevention and control at the farming side, and will become a powerful booster to promote the livestock industry towards modernization. The use of convolutional neural network after extracting a feature to complete the link according to the type of feature classification, then complete the data pre-processing, and using super pixel-based image segmentation and SIFT algorithm to complete image segmentation and image feature extraction, and finally through the convolutional neural network and support vector machine to complete the classification and prediction of animal action, driving the overall management level of the livestock industry to improve, and become an effective way to promote the development of intelligent animal husbandry.
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