A local-holistic graph-based descriptor for facial recognition

Metin Zontul

Face recognition remains critical and up-to-date due to its undeniable contribution to security. Many descriptors, the most vital figures used for face discrimination, have been proposed and continue to be done. This article presents a novel and highly discriminative identifier that can maintain high recognition performance, even under high noise, varying illumination, and expression exposure. By evolving the image into a graph, the feature set is extracted from the resulting graph rather than making inferences directly on the image pixels as done conventionally. The adjacency matrix is create ...Daha fazlası

Makale 2022 MULTIMEDIA TOOLS AND APPLICATIONS82 ( 13 ) , pp. 1 - 19298 178 Görüntülenme Süresiz Ambargo

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Multi-Class Document Classification Based on Deep Neural Network and Word2Vec

Metin Zontul

With the increase in unstructured data, the importance of classification of text-based documents has increased. In particular, the classification of news texts and digital documentation provides easy access to the information sought. In this study, a large amount of news textual data was used. After the data set was preprocessed, Bag of Words (BoW), TF-IDF, Word2Vec and Doc2Vec word embedding methods were applied. In the classification phase, Random Forest (RF), Multilayer Perceptron (MLP), Support Vector Machine (SVM) and Deep Neural Network (DNN) algorithms were applied. As a result of the e ...Daha fazlası

Makale 2022 JOURNAL OF AERONAUTICS AND SPACE TECHNOLOGIES15 ( 1 ) , pp. 5 - 65 81 Görüntülenme

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A Smart and Mechanized Agricultural Application: From Cultivation to Harvest

Metin Zontul

Food needs are increasing day by day, and traditional agricultural methods are not responding efficiently. Moreover, considering other important global challenges such as energy sufficiency and migration crises, the need for sustainable agriculture has become essential. For this, an integrated smart and mechanism-application-based model is proposed in this study. This model consists of three stages. In the first phase (cultivation), the proposed model tried to plant crops in the most optimized way by using an automized algorithmic approach (Sand Cat Swarm Optimization algorithm). In the second ...Daha fazlası

Makale 2022 Applied Sciences-Basel12 ( 12 ) 265 Görüntülenme

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Classification of Zinc-Coated Parts in Accordance with their Brightness Degree using Deep Learning Techniques

Metin Zontul

A novel technique was suggested to measure the brightness of the coated parts. The algorithm of Mask RCNN was used to detect the relevant region on the whole image. The pixels of black lines, which are associated with the brightness of the coating and reflected from the foreground, were counted using image processing technique. These pixels were used as the output in the machine learning training to classify the coated parts. The output was binarized to classify the coated plates as “Pass” and “Fail”. It was found that the RF model was the best model. The scores of its accuracy, F1, precision, ...Daha fazlası

Makale 2022 Journal of the Turkish Chemical Society Section B: Chemical Engineering5 , pp. 1 - 156 3 Görüntülenme

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2D Vector Representation of Binomial Hierarchical Tree Items

Metin Zontul | Seda Karateke

Today Artificial Intelligence (AI) algorithms need to represent different kinds of input items in numeric or vector format. Some input data can easily be transformed to numeric or vector format but the structure of some special data prevents direct and easy transformation. For instance, we can represent air condition using humidity, pressure, and temperature values with a vector that has three features and we can understand the similarity of two different air measurements using cosine-similarity of two vectors. But if we are dealing with a general ontology tree, which has elements "entity"as t ...Daha fazlası

Makale 2022 2022 International Conference On Theoretical And Applied Computer Science And Engineering (Ictasce) , pp. 1 - 126 130 Görüntülenme Süresiz Ambargo

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Automated evaluation of Cr-III coated parts using Mask RCNN and ML methodse

Metin Zontul

In this study, chrome coatings were carried out using a Cr-III electroplating bath. The coated parts were classified depending on their appearance. A new approach was developed to classify the coated parts automatically using artificial intelligence methods. Mask RCNN and machine learning (ML) methods such as Multilayer Perceptron (MLP), Support Vector Classifier (SVC), Gaussian Process (GP), K-nearest Neighbors (KNN), XGBoost, and Random Forest Classifier (RFC) were used together. Mask RCNN was used to clean the coated parts from the redundant data. The extracted data were flattened and conve ...Daha fazlası

Makale 2021 Surface & Coatings Technology422 833 Görüntülenme Süresiz Ambargo