Search Results - "Şengur, Abdulkadir"

Deep learning approaches for COVID-19 detection based on chest X-ray images by Ismael, Aras M., Şengür, Abdulkadir

“…[Display omitted] •A novel application is introduced, X-ray chest image based Covid-19 detection.•Deep learning approaches are used for Covid-19…”
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Evaluation of asphalt anti-cracking performance of SBS polymer with SCB method and deep learning by Yalcin, Erkut, Yilmaz, Mehmet, Demir, Fatih, Guzel, Baki, Ozdemir, Ahmet Munir, Şengur, Abdulkadir, Çambay, Ertuğrul

“…In recent years, there have been unprecedented developments in artificial intelligence. Object detection, voice recognition, face recognition etc. are some of…”
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Attention guided 3D CNN-LSTM model for accurate speech based emotion recognition by Atila, Orhan, Şengür, Abdulkadir

“…In this paper, a novel approach, which is based on attention guided 3D convolutional neural networks (CNN)-long short-term memory (LSTM) model, is proposed for…”
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Machine learning methods for cyber security intrusion detection: Datasets and comparative study by Kilincer, Ilhan Firat, Ertam, Fatih, Sengur, Abdulkadir

“…The increase in internet usage brings security problems with it. Malicious software can affect the operation of the systems and disrupt data confidentiality…”
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A novel image segmentation algorithm based on neutrosophic similarity clustering by Guo, Yanhui, Şengür, Abdulkadir

“…•This paper proposed a novel algorithm to segment the objects on images with or without noise.•Neutrosophic similarity function is defined to describe the…”
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A novel approach for accurate detection of the DDoS attacks in SDN-based SCADA systems based on deep recurrent neural networks by Polat, Hüseyin, Türkoğlu, Muammer, Polat, Onur, Şengür, Abdülkadir

“…•In the study, a data set specific to SDN-based SCADA architecture was obtained.•A novel systematic approach based on DDoS data is introduced.•Proposed model…”
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Exploring Deep Learning Features for Automatic Classification of Human Emotion Using EEG Rhythms by Demir, Fatih, Sobahi, Nebras, Siuly, Siuly, Sengur, Abdulkadir

“…Emotion recognition (ER) from Electroencephalogram (EEG) signals is a challenging task due to the non-linearity and non-stationarity nature of EEG signals…”
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Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation by Budak, Ümit, Guo, Yanhui, Tanyildizi, Erkan, Şengür, Abdulkadir

“…Liver and hepatic tumor segmentation remains a challenging problem in Computer Tomography (CT) images analysis due to its shape variation and vague boundary…”
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A novel retinal vessel detection approach based on multiple deep convolution neural networks by Guo, Yanhui, Budak, Ümit, Şengür, Abdulkadir

“…•This study formulates the retinal vessel detection task as a classification problem and solves it using a multiple classifier framework based on deep…”
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Convolutional neural networks based efficient approach for classification of lung diseases by Demir, Fatih, Sengur, Abdulkadir, Bajaj, Varun

“…Treatment of lung diseases, which are the third most common cause of death in the world, is of great importance in the medical field. Many studies using lung…”
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A retinal vessel detection approach using convolution neural network with reinforcement sample learning strategy by Guo, Yanhui, Budak, Ümit, Vespa, Lucas J., Khorasani, Elham, Şengür, Abdulkadir

“…Computer-aided detection (CAD) provides an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is an…”
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Computer-aided diagnosis system combining FCN and Bi-LSTM model for efficient breast cancer detection from histopathological images by Budak, Ümit, Cömert, Zafer, Rashid, Zryan Najat, Şengür, Abdulkadir, Çıbuk, Musa

“…Breast cancer (BC) is one of the most frequent types of cancer that adult females suffer from worldwide. Many BC patients face irreversible conditions and even…”
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An effective color image segmentation approach using neutrosophic adaptive mean shift clustering by Guo, Yanhui, Şengür, Abdulkadir, Akbulut, Yaman, Shipley, Abriel

“…Color image segmentation can be defined as dividing a color image into several disjoint, homogeneous, and meaningful regions based on the color information…”
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Transfer learning based histopathologic image classification for breast cancer detection by Deniz, Erkan, Şengür, Abdulkadir, Kadiroğlu, Zehra, Guo, Yanhui, Bajaj, Varun, Budak, Ümit

“…Breast cancer is one of the leading cancer type among women in worldwide. Many breast cancer patients die every year due to the late diagnosis and treatment…”
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Swin transformer-based fork architecture for automated breast tumor classification by ÜZEN, Hüseyin, FIRAT, Hüseyin, Atila, Orhan, ŞENGÜR, Abdulkadir

“…Breast cancer constitutes a prevalent and escalating health concern globally. Additionally, the significance of early diagnosis for effective treatment cannot…”
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Effective diagnosis of heart disease through neural networks ensembles by Das, Resul, Turkoglu, Ibrahim, Sengur, Abdulkadir

“…In the last decades, several tools and various methodologies have been proposed by the researchers for developing effective medical decision support systems…”
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The investigation of multiresolution approaches for chest X-ray image based COVID-19 detection by Ismael, Aras M., Şengür, Abdulkadir

“…COVID-19 is a novel virus, which has a fast spreading rate, and now it is seen all around the world. The case and death numbers are increasing day by day. Some…”
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A novel image thresholding algorithm based on neutrosophic similarity score by Guo, Yanhui, Şengür, Abdulkadir, Ye, Jun

“…•This study proposes a novel method to segment the objects on clear or noisy images.•The proposed approach performs well on images without noise or with…”
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KNCM: Kernel Neutrosophic c-Means Clustering by Akbulut, Yaman, Şengür, Abdulkadir, Guo, Yanhui, Polat, Kemal

“…The block diagram of the proposed Kernel-NCM approach. [Display omitted] •We proposed a new Kernel Neutrosophic c- Means (KNCM) algorithm for improving the NCM…”
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DCCMED-Net: Densely connected and concatenated multi Encoder-Decoder CNNs for retinal vessel extraction from fundus images by Budak, Ümit, Cömert, Zafer, Çıbuk, Musa, Şengür, Abdulkadir

“…Recent studies have shown that convolutional neural networks (CNNs) can be more accurate, efficient and even deeper on their training if they include direct…”
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