Zafer Cömert

Two-stage verification for multiinstance feature selection in dental anomaly detection: A convolutional neural network–gated recurrent unit approach with explainable artificial intelligence and optimization techniques

Zafer Cömert, Mesut Toğaçar, Alper Talha Karadeniz, Furkancan Demircan

tr (code pays fourni par la source)

Fatigue detection in performance sports with multivariate time series analysis: integrated use of wavelet transform and transformer models

Şadan Toğaçar, Mikâil Tel, Zafer Cömert

tr (code pays fourni par la source)

Integrating Adaptive Gaussian Precision and Multi-Scale Feature Extraction for Enhanced Diagnosis of Ph-Negative Myeloproliferative Neoplasms in BMT Images

Zafer Cömert, Hazel Işık, Muammer Türkoğlu, Abdulkadir Şengür

Philadelphia Chromosome (Ph)-negative myeloproliferative neoplasms (MPNs) are a critical subgroup of hematologic malignancies characterized by uncontrolled proliferation of myeloid cell lines in the bone marrow, leading to subtypes such as essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (MF). The study …

tr (code pays fourni par la source)

Classification of Maize Images Enhanced with Slot Attention Mechanism in Deep Learning Architectures

Zafer Cömert, Alper Talha Karadeniz, Erdal Başaran, Yüksel Çelik

Maize is a vital global crop, serving as a fundamental component of global food security. To support sustainable maize production, the accurate classification of maize seeds—particularly distinguishing haploid from diploid types—is essential for enhancing breeding efficiency. Conventional methods relying on manual inspection …

tr, us (code pays fourni par la source)

MobileNet- and attention-based MLP-Mixer architecture for geographical-region recognition of a marine fish (Perciformes: Carangidae) using otolith images

Ömerhan Dürrani, Seda İşgüzar, Andaç İmak, Tuncay Ateşşahin et autres

tr (code pays fourni par la source)

Enhanced Classification of Ear Disease Images Using Metaheuristic Feature Selection

Furkancan Demircan, Murat Ekіncі, Zafer Cömert, Eyup Gedikli

Ear diseases are characterized by various symptoms, including balance disturbances, delayed speech development in children, headaches, fever, and hearing loss. To prevent further complications, these conditions must be diagnosed and treated promptly. The traditional diagnostic method has been an otoscope examination by …

tr (code pays fourni par la source)

Convolutional Block Attention Module and Parallel Branch Architectures for Cervical Cell Classification

Zafer Cömert, Ferat Efil, Muammer Türkoğlu

ABSTRACT Cervical cancer persists as a significant global health concern, underscoring the vital importance of early detection for effective treatment and enhanced patient outcomes. While traditional Pap smear tests remain an invaluable diagnostic tool, they are inherently time‐consuming and susceptible to human …

az, tr (code pays fourni par la source)

Enhancing intra-aural disease classification with attention-based deep learning models

Furkancan Demircan, Murat Ekіncі, Zafer Cömert

Abstract Ear diseases are defined as pathological conditions that indicate dysfunction or abnormal function of the ear organ, which is part of the auditory system of living organisms that regulates hearing and balance functions. These diseases usually manifest as conditions that affect …

tr, az (code pays fourni par la source)

Filter-Based Image Enhancement Effects on CNN-Based Decision Support System for Cervical Cancer Diagnosis

Ferat Efil, Zafer Cömert

Cervical cancer is a type of cancer that begins in the cervix and spreads over time, typically associated with human papillomavirus (HPV) infection. This type of cancer can be prevented or treated with routine screening and early detection. The Pap smear test …

tr (code pays fourni par la source)

Computerized otoscopy image-based artificial intelligence model utilizing deep features provided by vision transformer, grid search optimization, and support vector machine for otitis media diagnosis

Zafer Cömert, Agnese Sbrollini, Furkancan Demircan, Laura Burattini

az, tr, it (code pays fourni par la source)

Sentiment Analysis based on Text with Universal Sentence Encoder and CNN-LSTM Models

Semih Osman Saka, Zafer Cömert

Text processing has a crucial role to perform in today’s information era for interpreting data and uncovering valuable insights. In this context, sentiment analysis is especially critical for evaluating customer satisfaction and feedback. The proposed work performs sentiment analysis on customer reviews …

tr (code pays fourni par la source)

Sinir Ağı Dil Modelleri ve Evrensel Cümle Kodlayıcı Kullanarak Havayolu Müşteri Yorumlarının Duygu Analizi

Semih Osman Saka, Zafer Cömert

Sentiment analysis represents a fundamental technique within the domain of natural language processing (NLP), employed for the purpose of discerning the emotional tenor of text-based data. Businesses may make strategic decisions by employing emotional insights derived from customer reviews to enhance customer …

tr (code pays fourni par la source)