Vücuttaki oksijen ihtiyacının farklı sebeplerle karşılanamaması durumunda ortaya çıkan anemi, 2023’de Dünya Sağlık Örgütü 500 milyondan fazla kişide görüldüğünü rapor etmiştir. Ayrıca, anemi dünyada en sık görülen kan hastalığıdır. Bu hastalığın önemli önlemlerinden biri erken teşhistir. Literatürde teşhis konusunda hızlı ve başarılı sonuçların elde edilebilmesi için makine öğrenmesi modelleri önerilmektedir. Ancak arzu edilen düzeyde etkin sonuçlar veremeyebilir. Optimizasyon algoritmaları...

The high resolution hyperspectral remote sensing data collected from urban and landscape areas have been extensively studied over the past decades. Recent applications pose an emerging need of analyzing land cover types based on originating sensory devices. Toward this goal, we propose a deep neural network (DNN) classifier in paper. DNN is constructed by combining stacked autoencoder with desired numbers autoencoders softmax classifier. Our experimental results demonstrate that presented...

Magnetoencephalography (MEG) is an emerging medical signal processing methodology that uses the magnetic field of brain to decode internal activity. However, MEG signals are very complicated and usually corrupted with significant amount noise. Therefore, it not easy directly understand how human responds visual stimulus by analysing without utilizing advanced techniques such as feature extraction classification. The can be accomplished applying Riemannian approach. Moreover, extracted...

Salt and pepper (SAP) noise elimination is a crucial step for further image processing pattern recognition applications. The main aim of this article to propose novel SAP method which employs regression-based neuro-fuzzy network highly corrupted gray scale color images. In the proposed method, multiple filters trained with artificial bee colony algorithm combined decision tree algorithm. performance filter compared number well known methods respect popular metrics including, structural...

Abstract Oil leakage between the slipper and swash plate of an axial piston pump has a significant effect on efficiency pump. Therefore, it is extremely important that any can be predicted. This study investigates leakage, oil film thickness, pocket pressure values with circular dimples under different working conditions. The results reveal flat slippers suffer less than those textured surfaces. Also, deep learning-based framework proposed for modeling behavior. long short-term memory-based...

Melanoma is a serious cancer that causes many people to lose their lives. This disease can be diagnosed by dermatologist as result of interpretation the dermoscopy images ABCD rule. In this study, deep neural network (DNN) used new method for diagnosis melanoma skin cancer. compared with the-state-art-methods in literature. According obtained results, DNN was more successful than comparative methods.

This paper investigates the application of a deep neural network architecture that consists stackted autoencoder with two autoencoders and softmax layer for purpose human activity classification. Th performance proposed is tested on commonly used data set known as Human Activity Recognition Using Smartphones. It observed method yields better classification results than representative state-of-the-art methods provided parameters are suitably optimized.

Parkinson’s disease is accepted as one of the most important diseases in world. can be diagnosed various conventional techniques. Recently, these techniques have been replaced by artificial intelligence systems. This study proposes a feature selection and classification technique for based on speech signals using meta-heuristic algorithm. The proposed method selects features from data set including signal that accurately represent problem efficient search strategies immune plasma algorithm...

Parkinson hastalığının en önemli belirtilerinden birisi konuşma bozukluklarıdır. Dolayısıyla, ses sinyallerinden problemi temsil edebilecek özniteliklerin çıkarılması ile hastalık sınıflandırılabilmektedir. Makine öğrenmesi teknikleri sınıflandırma problemlerinde oldukça başarılı sonuçlar üretmektedir. Bu çalışmada, sinyalleri üzerinden sınıflandırılmasında, KYK, ROS, DVM, NB ve KA makine tekniklerinin başarımının araştırılması amaçlanmıştır. amaç için literatüre yeni sunulan yüksek boyutlu...

The prediction of the hand movement based on Electromyography (EMG) signals has been extensively studied over past three decades. However, recent EGM applications pose an emerging need efficient classification EMG signals. Toward this goal, we propose a deep neural network (DNN) classifier in study to classify 6 different from DNN ability extract new features raw data and reduce dimension set. Our experimental results human subjects demonstrate that can efficiently accurately distinguish movement.

In recent years, computer vision systems have been used in almost every field of industry. this study, image processing algorithm has developed by using CUDA (GPU) which is 79 times faster than CPU. We had accelerated destemming process pepper. 65 percent total national production pepper produced our cities, Kahramanmaras and Gaziantep Turkey. Firstly, hybrid intuitionistic fuzzy edge detection for preprocessing original Otsu method determining automatic threshold algorithm. Then the...

Corneal ulcer is one of the most devastating eye diseases causing permanent damage. There exist limited soft techniques available for detecting this disease. In recent years, deep neural networks (DNN) have significantly solved numerous classification problems. However, many samples are needed to obtain reasonable performance using a DNN with huge amount layers and weights. Since collecting data set large number usually difficult time-consuming process, very large-scale pre-trained DNNs,...

Parkinson's disease can be diagnosed by the speech signals. In general, data obtained feature extraction algorithms from signals are used in any classification algorithm. Some of extracted features have a high ability to represent relevant problem, while others low. diagnosis disease, it is very important determine which may increase performance. this paper, Artificial Bee Colony algorithm based selection approach proposed for solution mentioned problem. The method has been analyzed...

Intuitionistic fuzzy edge detection algorithm has been used for the signification or characterization of images. It designed by experts and provides to aim minimize errors. However, it a fixed value thresholding. In this paper, hybrid developed using Otsu method which is calculated threshold depending on To be applicable in parallel intuitionistic pave way accelerating performing graphics card. logic tested transferring different size images cards computing capacity via Compute Unified...

Günümüzde artan sanayileşme ve nüfus, atık sayısının artması sebep olmuştur. Bununla birlikte atıkların yönetilebilirliği zorlaşmıştır. Dolayısıyla yönetimi geri dönüşüm süreçleri büyük bir önem kazanmaktadır. Fakat, hızla nüfus tespit sürelerinin artmasına zorlaşmasına olmaktadır. Geliştirilmiş nesne sistemleri; doğru şekilde sınıflandırılmasını, süreçlerinin verimliliğini artırılmasına çevreye olan olumsuz etkileri azaltılmasında önemli rol oynamaktadır. Bu çalışmada, dönüşümlü tespiti...

The effect of using autoencoders for dimensionality reduction a medical data set is investigated. A stack two has been trained popular benchmark dermatological disease diagnosis. improvement the presented approach visualized by Principal Component Analysis method. Results shows that use significantly improves accuracy