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Brain tumor is a progressive disease that significantly affects human life. These diseases can reduce the quality of life by causing losses in motor and cognitive functions. Since the chance of treatment decreases when not diagnosed early, advanced technologie…

Early detection of lung cancer remains a critical challenge in medical imaging, where accurate classification between benign and malignant pulmonary nodules can significantly impact patient outcomes. This study presents a comprehensive comparative analysis of …

Diabetic retinopathy is the leading cause of blindness among diabetic patients. It occurs when the light-sensitive tissue in the retina is damaged. According to WHO statistics, the current global prevalence of diabetic retinopathy is approximately 103 million …

Accurate and transparent blood glucose forecasting is crucial for effective diabetes management. This paper presents an interpretable deep learning (DL) framework based on multi-task learning (MTL) for forecasting glucose levels at multiple prediction horizons…

Diabetes is a chronic disease affecting millions worldwide, necessitating early and accurate diagnosis for effective management. Traditional diagnostic methods, while reliable, often struggle with efficiency and early-stage detection. Deep learning has emerged…

Bu çalışmada, el yazısı karakterlerin tanınmasına yönelik derin öğrenme tabanlı bir model geliştirilmiştir. Model, farklı sayıda çıkış sınıfı (karakter) için test edilmiş; yalnızca 10 karakterin sınıflandırıldığı senaryoda %96 doğruluk oranı elde edilirken, sı…

The COVID-19 pandemic has necessitated the development of rapid, accurate, and automated diagnostic tools to assist healthcare professionals in patient screening and management. This comprehensive study presents a detailed comparative analysis of ten state-of-…

Bitkilerde hastalıkların erken teşhisi, tarımsal verimliliğin artırılması ve ürün kayıplarının önlenmesi açısından büyük öneme sahiptir. Bu çalışmada, tarımsal üretimde önemli kayıplara yol açan bitki yaprak hastalıklarının erken teşhisine yönelik bir yapay ze…

Robust object detection and classification in dynamic industrial scenarios is still a challenge, in particular if the system has to work in real-time on mid-ranged hardware. Classical vision-based methods have difficulties to cope with low/weak illumination, r…

This study presents a Hybrid Digital-Physical Risk Management Framework designed to enhance urban climate resilience through the integration of Industry 4.0 technologies. By combining real-time IoT sensor networks, AI-based predictive analytics, and blockchain…

We developed a series of financial social media sentiment analysis models starting with PyFin-Sentiment, a recent state-of-the-art domain-specific large language model for the financial domain. We focused on label accuracy and improvements in the quality and q…

Yapay zeka (YZ), tasarım sürecinden karar destek sistemlerine, maliyet analizinden malzeme tespitine kadar pek çok alanda kullanılmakta; tarihi yapılarda ise malzeme bozulmalarının tespiti, restorasyon süreçlerinin iyileştirilmesi ve kültürel varlıkların belge…

Maritime vessel detection in satellite images address real time issues such as maritime security, illegal fishing and environmental monitoring, which require efficient tracking of vessels in large scale. Maritime vessel detection is challenged by limited annot…

Sunulan çalışmada, kalp hastalığı riskinin erken ve güvenilir biçimde tahmin edilmesini sağlayan makine öğrenmesi tabanlı bir mobil uygulama geliştirilmiştir. Dokuz farklı algoritma değerlendirilmiş, en yüksek doğruluğa (%86,81) sahip olan k-NN modeline rağmen…

Kent meydanları, toplumsal hareketliliğin ve kamusal katılımın merkezinde yer alarak bireyler arası sosyal ilişkileri güçlendiren, çok işlevli etkinliklere ev sahipliği yapan kamusal mekânlardır. Kitlelerin kesişim noktasını oluşturan meydanlar, kullanıcı odak…

Efficient semantic segmentation and compression of 3D point cloud data are essential for enabling scalable, real-world applications involving large-scale LiDAR environments. This work presents a lightweight hybrid framework that integrates point transformer v3…

In this study, a classification problem is discussed to predict whether individuals' annual income levels are above $50,000. The UCI Adult Income Dataset, which is derived from the 1994 US Census (Census) data and is widely used in the field of machine learnin…

Generative Artificial Intelligence is gaining popularity every day and uses contextual data to personalize and enhance user experiences. This paper explores music generation that is conditioned on weather. It influences musical compositions by connecting MIDI …

Predictive maintenance (PdM) enhances industrial operational efficiency by facilitating timely detection of equipment failures using machine learning models developed from historical maintenance data.  Real-world industrial datasets frequently exhibit signific…

Healthcare fraud, waste, and abuse (FWA) are among the most significant drivers of financial inefficiency in healthcare systems worldwide, with estimates suggesting they contribute to as much as 10% of total healthcare expenditures. In the United States, these…