7 papers
A Novel Public Dataset for Strawberry (Fragaria x ananassa) Ripeness Detection and Comparative Evaluation of YOLO-Based Models
Mustafa Yurdakul, Zeynep Sena Bastug, Ali Emre Gok +1
The strawberry (Fragaria x ananassa), known worldwide for its economic value and nutritional richness, is a widely cultivated fruit. Determining the correct ripeness level during t…
A Mobile Application for Flower Recognition System Based on Convolutional Neural Networks
Mustafa Yurdakul, Enes Ayan, Fahrettin Horasan +1
A convolutional neural network (CNN) is a deep learning algorithm that has been specifically designed for computer vision applications. The CNNs proved successful in handling the i…
CoAtNeXt:An Attention-Enhanced ConvNeXtV2-Transformer Hybrid Model for Gastric Tissue Classification
Mustafa Yurdakul, Sakir Tasdemir
Background and objective Early diagnosis of gastric diseases is crucial to prevent fatal outcomes. Although histopathologic examination remains the diagnostic gold standard, it is…
MRI-Based Brain Tumor Detection through an Explainable EfficientNetV2 and MLP-Mixer-Attention Architecture
Mustafa Yurdakul, Åakir TaÅdemir
Brain tumors are serious health problems that require early diagnosis due to their high mortality rates. Diagnosing tumors by examining Magnetic Resonance Imaging (MRI) images is a…
An Enhanced YOLOv8 Model for Real-Time and Accurate Pothole Detection and Measurement
Mustafa Yurdakul, Åakir Tasdemir
Potholes cause vehicle damage and traffic accidents, creating serious safety and economic problems. Therefore, early and accurate detection of potholes is crucial. Existing detecti…
Triple-Stream Deep Feature Selection with Metaheuristic Optimization and Machine Learning for Multi-Stage Hypertensive Retinopathy Diagnosis
Suleyman Burcin Suyun, Mustafa Yurdakul, Sakir Tasdemir +1
Hypertensive retinopathy (HR) is a severe eye disease that may cause permanent vision loss if not diagnosed early. Traditional diagnostic methods are time-consuming and subjective,…