Recognition of dog breeds using convolutional neural network and visual geometry group

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Abstract

Due to excessive breeding or cross-breeding, the nature of an animal like a dog has varied a lot from years ago. Using Image processing for the breed analysis will predict the exact result/s with maximum accuracy, unlike naked eye recognition ADA boosting methodology is used for breed analysis and recognition. ADA Boosting creates a strong classifier from several weak classifiers. To separate the dog breeds from one another, we use Image processing classification. It predicts the predominant breed/s present in the canine with maximum accuracy. Since the dogs may be cross-breed or had cross-breed predecessors, they may have a variety of breeds present in them, so using Image processing Classification tools we find the correct breed/s. It will be essential for easy classification of the dogs based on breeds and it can provide proof that naked eye recognition of breeds is undependable or trivial. Using Image processing analysis, we can analyze and do recognition of various animals like sheep, cattle, etc.

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Sharma, A., Sahoo, A., Azhagiri, M., & Dutta, D. (2019). Recognition of dog breeds using convolutional neural network and visual geometry group. International Journal of Engineering and Advanced Technology, 9(1), 3898–3902. https://doi.org/10.35940/ijeat.A1263.109119

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