Ara
Toplam kayıt 11, listelenen: 1-10
Context-Sensitive Model Learning for Lung Nodule Detection
(2016)
Nodule detection in chest radiographs is a main component of current Computer Aided Diagnosis (CAD) systems. The problem is usually approached as a supervised classification task of candidate nodule segments. To this end, ...
Development of a MFCC-SVM Based Turkish Speech Recognition System
(2016)
In this study, a SVM-MFCC based Turkish Speech Recognition system is devoloped. In the structure, Mel Frequency Cepstral Coefficients (MFCC) are used for feature extraction and Support Vector Machines(SVM) are used for ...
Using Machine Learning Methods in Early Diagnosis of Breast Cancer
(2021)
Breast cancer is one of the most important health diseases to be treated in the world, and it is a subject that has a wide place in research subjects. In this study, results are provided by using seven different machine ...
Classification of Different Objects with Artificial Neural Networks Using Electronic Nose
(2015)
In this paper; an e-nose with low cost which consisting of 8 different gas sensors was used and with this e-nose 9 different odors ((mint, lemon, egg, rotten egg, angelica root, nail polish, naphthalene, rose water, and ...
Wi-Fi Based Indoor Positioning System with Using Deep Neural Network
(2020)
Indoor positioning is one of the major challenges for the future large-scale technologies. Nowadays, it has become an attractive research subject due to growing demands on it. Several algorithms and techniques have been ...
Obstructive Sleep Apnea Classification with Artificial Neural Network Based On Two Synchronic Hrv Series
(2015)
In the present study, "obstructive sleep apnea (OSA) patients" and "non-OSA patients" were classified into two groups using with two synchronic heart rate variability (HRV) series obtained from electrocardiography (ECG) ...
Sparsity-driven weighted ensemble classifier
(2018)
In this study, a novel sparsity-driven weighted ensemble classifier (SDWEC) that improves classification accuracy and minimizes the number of classifiers is proposed. Using pre-trained classifiers, an ensemble in which ...
Applications of Deep Learning Techniques to Wood Anomaly Detection
(2022)
Wood products and structures have an important place in today's industry. They are widely used in many fields. However, there are various difficulties in production systems where wood raw material is under many processes. ...
Detection of multiple sclerosis from photic stimulation EEG signals
(2021)
Background: Multiple Sclerosis (MS) is characterized as a chronic, autoimmune and inflammatory disease of the central nervous system. Early diagnosis of MS is of great importance for the treatment and course of the disease. ...