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The investigated feature techniques are Zernike Moments, local binary pattern, Gabor filter, and Haralick texture moments. The normalised feature vector is used to examine whether deep learning using convolutional neural network is better at identifying the ear than other commonly used machine learning techniques. The widely used machine learning techniques that were used to compare them are decision tree, na\u00efve Bayes, K-nearest neighbors (KNN), and support vector machine (SVM). This paper proved that using a bag of feature techniques and the classification technique of deep learning using convolutional neural network was better than standard machine learning techniques. The result achieved by the deep learning using convolutional neural network was 92.00% average ear identification rate for both left and right ears.<\/jats:p>","DOI":"10.1155\/2022\/9692690","type":"journal-article","created":{"date-parts":[[2022,8,17]],"date-time":"2022-08-17T20:05:07Z","timestamp":1660766707000},"page":"1-17","source":"Crossref","is-referenced-by-count":8,"title":["Ear Biometrics Using Deep Learning: A Survey"],"prefix":"10.1155","volume":"2022","author":[{"given":"Aimee","family":"Booysens","sequence":"first","affiliation":[{"name":"School of Mathematics, Statistics & Computer Science, University of KwaZulu-Natal, Durban, South Africa"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2850-8645","authenticated-orcid":true,"given":"Serestina","family":"Viriri","sequence":"additional","affiliation":[{"name":"School of Mathematics, Statistics & Computer Science, University of KwaZulu-Natal, Durban, South Africa"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1145\/2431211.2431221"},{"key":"2","volume-title":"Ear Biometrics","author":"B. 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