Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Conference Object Deep Learning Model for Fingerprint Biometric Identification System(Institute of Electrical and Electronics Engineers Inc., 2025) Abdulkarim, Anas; Ulu, Eren; Sever, HayriConference Object Spam Detection With Fasttext Based Features(Institute of Electrical and Electronics Engineers Inc., 2024) Karadeniz, T.; Tokdemir, G.; Maraş, H.H.Fasttext is a powerful word representation method that creates word representations based on vectors of character n-grams. In this work, we propose a method that utilizes fasttext features for a novel feature engineering model for the spam detection problem. In the feature engineering method, the combination of average, mean of second derivative; mean peak and standard deviation of fasttext features are computed. Finally, tf-idf features are also considered for the modeling process. The success of each feature engineering technique is measured and reported. The combination of the five feature extraction methods, tested on two spam detection datasets, yielded promising results with an accuracy of 0.978 on e-mail spam detection and an accuracy of 0.986 on sms spam classification. © 2024 IEEE.Conference Object Citation - Scopus: 1An Isolated Word Speaker Recognition System(Institute of Electrical and Electronics Engineers Inc., 2017) Ozaydin, S.The paper presents a design of an isolated word speaker recognizer system by using the Hidden Markov Model. HTK toolkit is used as a design tool. The system is operated on a closed set of speakers and with a limited vocabulary of words. Digit utterances from one to ten with ten speakers (7 male, 3 female) are used as dataset in the system. It consists of isolated words that are separated by silences. Each speaker reads each word ten times. Six of them are used in training and the remaining are used in the test phase. The Mel cepstral coefficients are used in order to design the acoustic features and HMM models are constructed. A threshold calculation is performed for each speaker. After threshold adjustment, tests are performed for the performance evaluation and accuracy rates are calculated for each user. The system resulted in changing levels of recognition accuracy for each speaker and each word. © 2017 IEEE.