Transfer Learning on Convolutional Neural Networks for Dog Identification

Xinyuan Tu, K. Lai, S. Yanushkevich
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引用次数: 13

Abstract

This paper considers application of machine learning in the context of animal identity management for veterinary practice. In this application, electronic medical records of animals would include digital photographs that are used to identify them using image processing and recognition technologies. We investigated how combination of the “soft” biometrics such as breed, as well as face biometrics of dogs can improve identification of dogs. We apply transfer learning on GoogLeNet to perform the breed classification on the proposed BreedNet, and then to identify individual dogs within the classified breeds, on the proposed DogNet.
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基于卷积神经网络的狗狗识别迁移学习
本文考虑机器学习在兽医实践中动物身份管理背景下的应用。在这个应用程序中,动物的电子医疗记录将包括使用图像处理和识别技术来识别它们的数字照片。我们研究了如何结合狗的“软”生物特征,如品种,以及狗的面部生物特征来提高狗的识别。我们在GoogLeNet上应用迁移学习,在提议的BreedNet上执行品种分类,然后在提议的DogNet上识别分类品种中的单个狗。
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