This paper addresses the problem of biometric identification of animals, specifically dogs . We apply advanced machine learning models such as deep neural network on the photographs of pets in order to determine the pet identity . The proposed network is able to achieve an accuracy of 90.80% and 91.29% when differentiating between the two dog breeds, for two different datasets . Without the use of “soft” biometrics, the identification rate of dogs is 78.09% but by using a decision network to incorporate ‘soft’ biometricities, such as breed, height, or gender, in fusion with ‘hard’ photos of the pet’s face. We apply the principle of transfer learning

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Keywords : network - soft - identification - biometrics - pet -

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