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19 results for “SVM”

Research Article Open Access Improving Computational Performance of Least Squares Multiple Birth Support Vector Machines with k-Means Clustering
Güvenç Arslan, Arslan G, Nisa Nur Bülbül, Bülbül N
Cognitive Models and Artificial Intelligence Conference 2023 https://doi.org/10.36287/setsci.6.1.010

Multiple Birth Support Vector Machines (MB-SVM) were introduced as a powerful extension of SVM. Although the basic idea is like SVM, optimal non-parallel hyperplanes are used for each class category. One may find different implementations of this approach in t…

Research Article Open Access XAI-Powered Comparative Diabetes Prediction with XGBoost, SVM and Artificial Neural Networks
Furkan Sefa Demirci, Demirci F, Remzi Yıldırım, Yıldırım R
International Symposium on AI-Driven Engineering Systems 2025 https://doi.org/10.36287/setsci.22.30.001

In this study, diabetes prediction was conducted using XGBoost, Support Vector Machines (SVM), and a Multilayer Artificial Neural Network (ANN). Attributes that cannot be biologically ‘0’ (e.g. glucose, BMI) were first marked as NaN. After filling the missing …

Research Article Open Access Improving Hyperspectral Image Classification with Watershed Segmentation-Based Texture Features
Çiğdem Şerifoğlu Yılmaz, Şerifoğlu Yılmaz Ç, Volkan Yılmaz, Yılmaz V, Oğuz Güngör, Güngör O
2nd International Symposium on Innovative Approaches in Scientific Studies 2018

Hyperspectral images offer a good separability among land cover classes, owing to their advantages to provide spectral bands with narrow wavelength intervals. It is also possible to further increase classification accuracy of hyperspectral images by integrat…

Research Article Open Access Multilingual Sentiment Analysis for Mobile Gaming: A Comparative Study of Machine Learning and Hybrid Deep Learning Approaches
Erol Kına, Kına E, Recep Özdağ, Özdağ R
International Trend of Tech Symposium 2024 https://doi.org/10.36287/setsci.21.1.001

The rapid expansion of the mobile gaming industry has underscored the need to understand user sentiment, with social media platforms like X (Twitter) providing key insights. This study applied sentiment analysis to English and Turkish tweets, utilizing the TEM…

Research Article Open Access Development of Machine Learning-Based Sales Cancellation/Return Forecasting Models for the E-Commerce Industry
Zehra Sude Sarı, Sarı Z, Batuhan Taşkapı, Taşkapı B, Gökay Dağdaş, Dağdaş G, Mehmet Fatih Akay, Akay M
International Conference on Advances in Electrical-Electronics Engineering and Computer Science 2024 https://doi.org/10.36287/setsci.19.5.022

E-commerce is evolving rapidly, creating a more competitive market environment. With this development, gaining a competitive advantage has become even more crucial. Companies implement various strategic moves to maintain their position in this competitive mark…

Research Article Open Access Crop Yield Prediction Using Machine Learning Algorithms
G. Malini Devi, Devi G, Badhe Siri Vennela, Vennela B, Shreya Arukala, Arukala S, Sai Amogha Uppalapati, Uppalapati S, Kambalapally Anudeepthi, Anudeepthi K
Proceeding of the Cognitive Models and Artificial Intelligence Conference 2024 https://doi.org/10.36287/setsci.17.1.0040

The study will utilize machine learning algorithms such as Random Forest, Gradient Boosting, and Support Vector Regression (SVR) on data collected from the districts of Nalgonda, Yadadri Bhuvanagiri, and Suryapet over the past two years. The project seeks to m…

Research Article Open Access Recognition of Handwritten Source Code Characters With Deep Neural Networks
Barış Kılıçlar, Kılıçlar B, Metehan Makinacı, Makinacı M
4th International Symposium on Innovative Approaches in Engineering and Natural Sciences 2019 https://doi.org/10.36287/setsci.4.6.111

In this paper we presents an application of deep learning techniques to recognize handwritten source code characters. Although there are many works on the handwritten character recognition (HCR) problem, very few works have been done about the offline handwrit…

Research Article Open Access Akut Lenfoblastik Löseminin Makine Öğrenimi ile Sınıflandırılması
Ayşe Berika Varol Malkoçoğlu , Varol Malkoçoğlu  A, İsmail İşeri, İşeri İ
4th International Symposium on Innovative Approaches in Engineering and Natural Sciences 2019 https://doi.org/10.36287/setsci.4.6.139

Akut Lenfoblastik Lösemi (ALL) genellikle 2-5 yaş arasındaki çocuklarda görülen, kemik iliğindeki beyaz kan hücrelerinin hızlı artışından ve şekilsel bozukluklarından kaynaklanan bir kanser türüdür. Tespit edilip tedavi sürecinin başlatılmadığı takdirde ölümle…

Research Article Open Access Support Vector Machine Classifier of Grain Stored in Silo-bags by Using Wireless Network of Temperature and Moisture Sensors
Shawqi Mohammed Othman Farea, Mohammed Othman Farea S, Muzaffer   Kanaan, Kanaan M
International Congress on Human-Computer Interaction, Optimization and Robotic Applications 2019 https://doi.org/10.36287/setsci.4.5.003

We propose using support vector machines (SVMs) as a machine learning classifier in a grain-conditionmonitoring system. This system is used to proactively monitor the silobag-stored grain condition. The system consists of a wireless sensor network (WSN) and a …

Research Article Open Access Enhancing Offline Handwritten Signature Identification with Pre-Trained CNN Architectures
Nader Ebrahimpour, Ebrahimpour N
Proceeding of the Cognitive Models and Artificial Intelligence Conference 2024 https://doi.org/10.36287/setsci.17.1.0030

Handwritten Signature Recognition (HSR) is a vital task in document authentication and verification systems. This paper proposes a novel approach for offline HSR leveraging pre-trained Convolutional Neural Network (CNN) models. CNNs have demonstrated remarkabl…

Research Article Open Access Skin Cancer Classification into Three Classes
Cihan Akyel, Akyel C
Proceedings of the 6th International Symposium on Innovative Approaches in Smart Technologies 2022 https://doi.org/10.36287/setsci.5.2.008

The incidence of skin cancer is increasing. Early detection of cases of skin cancer is vital for treatment. Recently, computerized methods have been widely used in cancer diagnosis. These methods have important advantages such as no human error, short diagnosi…

Research Article Open Access Comparison of Control Methods Approaches in Microgrid Architectures
Ayşe Bağıran, Bağıran A, Köksal Erentürk, Erentürk K
4th International Symposium on Innovative Approaches in Engineering and Natural Sciences 2019 https://doi.org/10.36287/setsci.4.6.070

A microgrid is a power grid consists of distributed power generation units and loads. Microgrid is also a system that can operate in grid-connected mode and islanding (autonomous) mode. The control of distributed power generation units in microgrids is necessa…

Research Article Open Access Meme Kanserinin Makine Öğrenmesi Yöntemleri İle İkili Sınıflandırılması
Hakan Kör, Kör H
4th International Symposium on Innovative Approaches in Engineering and Natural Sciences 2019 https://doi.org/10.36287/setsci.4.6.145

Bu çalışmada, 596 kayıt ve 31 sütundan oluşan veri setiyle R programlama dili üzerinde akciğer kanserinin ikili sınıflama başarısı test edilmiştir. İlk aşama veri setinin temizlemesi, boş değerlerin kaldırılması ve verilerin denetlenmesinden oluşmaktadır. Daha…

Research Article Open Access Word Vector Space for Text Classification and Prediction According to Author
İlknur Dönmez, Dönmez İ, Elnaz Pashaei , Pashaei  E, Elham Pashaei 
International Congress on Human-Computer Interaction, Optimization and Robotic Applications 2019 https://doi.org/10.36287/setsci.4.5.021

Word embedings are intense vector representations of words. They capture the semantic order between words. In our study, we propose a new method for classifying text by author, using word embeds and author vector space. Using each author's books, we trained th…

Research Article Open Access A Mobile Robot Application for 3D Object Classification via Point Cloud Data in Indoor Environment
Fatma Caran, Caran F, Güleycan Tuğrul, Tuğrul G, Ümit Göven, Göven Ü, Kaya Turgut, Turgut K, Burak Kaleci, Kaleci B
International Congress on Human-Computer Interaction, Optimization and Robotic Applications 2019 https://doi.org/10.36287/setsci.4.5.038

3D object classification has been widely studied in robotic community in recent years. According to types of features that are utilized to describe an object, 3D object classification studies can be separated into two main categories (local and global).The loc…

Research Article Open Access Kompleks Değerli Yapay Sinir Ağları ile Kardiotokogram Verisinde Morfolojik Örüntü Sınıflandırma
Eda  Çapa Kızıltaş  , Çapa Kızıltaş   E, Ayşenur  Uzun  , Uzun   A, Ersen  Yılmaz  , Yılmaz   E
3rd International Symposium on Innovative Approaches in Scientific Studies (Engineering and Natural Sciences) 2019

Bu çalışmada UCI Makine Öğrenmesi havuzundan alınan kardiotokogram verisinde morfolojik örüntü sınıflandırması yapılmıştır. Sınıflandırıcı olarak kompleks değerli yapay sinir ağları kullanılmıştır. Sınıflandırıcının performansı 10-katlı çapraz doğrulama yaklaş…

Research Article Open Access A Performance Analysis of Extreme Learning Machine on Skin Segmentation Dataset
Ayşenur  Uzun  , Uzun   A, Eda Çapa  Kızıltaş  , Kızıltaş   E, Ersen  Yılmaz  , Yılmaz   E
3rd International Symposium on Innovative Approaches in Scientific Studies (Engineering and Natural Sciences) 2019

Digital image processing has become popular research area recently because of its widespread application compatibility such as security, robotics, quality control, face authentication. Skin segmentation methodology, which is a tool of digital image processing,…

Research Article Open Access Fine-Tuning Models Comparisons on Garbage Classification for Recyclability
Umut Özkaya, Özkaya U, Levent Seyfi, Seyfi L
2nd International Symposium on Innovative Approaches in Scientific Studies 2018

In this study, it is aimed to develop a deep learning application which detects types of garbage into trash in order to provide recyclability with vision system. Training and testing will be performed with image data consisting of several classes on differen…

Research Article Open Access Structured Deep Learning Supported with Point Cloud for 3D Human Pose Estimation
Erdal Özbay, Özbay E, Ahmet Çınar, Çınar A, Zafer Güler, Güler Z
International Symposium on Multidisciplinary Studies and Innovative Technologies 2017

In this paper, a structural-output is obtained to estimate 3D human pose using 3D human point cloud and monocular images. The Neural Network takes a human image and 3D pose as inputs and gives outputs a score value. Conditional Random Field (CRF) approach is u…

Research Contributions (2019+)Peer reviewed by at least two reviewers
Open AccessCC BY 4.0
Open Discovery Metadata · DOI · OAI-PMH
Global Reachresearchers worldwide