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It is targeted to distinguish the gender of the person and to obtain information about the person is children or adults by making essential works on the images. Convolutional neural network (CNN) is one of the deep face recognition algorithms that widely used to recognize facial images. This study is suggested as a study that detects noise in images using the fuzzy logic-based filter method and classifies this cleared data by gender using the matrix completion and CNN. TensorFlow which is a machine learning library that used to train and tests deep learning methods is used for experiments. The customer photographs taken during using the system are transformed into a matrix expression through a system trained using this algorithm. The obtained results indicated that the offered technique detects age and gender with a 96% accuracy value and 1.145 seconds time.<\/jats:p>","DOI":"10.3233\/jifs-219206","type":"journal-article","created":{"date-parts":[[2021,7,10]],"date-time":"2021-07-10T04:58:38Z","timestamp":1625893118000},"page":"491-501","source":"Crossref","is-referenced-by-count":4,"title":["Age group and gender classification using convolutional neural networks with a fuzzy logic-based filter method for noise reduction"],"prefix":"10.1177","volume":"42","author":[{"given":"Ali","family":"Tunc","sequence":"first","affiliation":[{"name":"Kuveyt T\u00fcrk Participation Bank, Konya R&D Center, Konya, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sakir","family":"Tasdemir","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, Faculty of Technology, Selcuk University, Konya, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Murat","family":"Koklu","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, Faculty of Technology, Selcuk University, Konya, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmet Cevahir","family":"Cinar","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, Faculty of Technology, Selcuk University, Konya, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-219206_ref1","doi-asserted-by":"crossref","unstructured":"Albiero V. , Ks K. , Vangara K. , Zhang K. , King M.C. and Bowyer K.W. , Analysis of gender inequality in face recognition accuracy, in: Proceedings of the IEEE Winter Conference on Applications of Computer Vision Workshops (2020), 81\u201389.","DOI":"10.1109\/WACVW50321.2020.9096947"},{"key":"10.3233\/JIFS-219206_ref2","first-page":"1","article-title":"Criminal tendency detection from facial images and the gender bias effect","volume":"7","author":"Hashemi","year":"2020","journal-title":"Journal of Big Data"},{"key":"10.3233\/JIFS-219206_ref3","doi-asserted-by":"crossref","unstructured":"Mittal S. and Mittal S. , Gender Recognition from Facial Images using Convolutional Neural Network, in: 2019 Fifth International Conference on Image Information Processing (ICIIP), IEEE, (2019), 347\u2013352.","DOI":"10.1109\/ICIIP47207.2019.8985914"},{"key":"10.3233\/JIFS-219206_ref4","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/s11554-017-0714-3","article-title":"Deepgender: real-time gender classification using deep learning for smartphones","volume":"16","author":"Haider","year":"2019","journal-title":"Journal of Real-Time Image Processing"},{"key":"10.3233\/JIFS-219206_ref6","unstructured":"Szilagyi L. , Benyo Z. , Szil\u00e1gyi S.M. and Adam H. , MR brain image segmentation using an enhanced fuzzy c-means algorithm, in: Proceedings of the 25th annual international conference of the IEEE engineering in medicine and biology society (IEEE Cat. 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