Air quality forecasting is critical for environmental monitoring and public health, and in this study, we propose a hybrid approach utilizing Gooseneck Barnacle Optimization (GBO) and Artificial Neural Networks (ANN) ...
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Multimodal domain adaptation (MMDA) aims to transfer knowledge across different domains that contain multimodal data. Current methods typically assume that both the source and target domains have paired multimodal dat...
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Aspect-based sentiment analysis (ABSA) is a natural language processing (NLP) technique to determine the various sentiments of a customer in a single comment regarding different aspects. The increasing online data con...
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software component selection is one of the most challenging problems for software developers to meet customer needs. Despite various methods researchers propose to aid in component selection, a gap exists in addressin...
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Intracranial hemorrhage (ICH) is a life-threatening condition that requires rapid and accurate diagnosis to improve treatment outcomes and patient survival rates. Recent advancements in supervised deep learning have g...
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Hearing-impaired people undergo auditory brainstem response (ABR) testing to assess their peripheral auditory nerve system. Audiologists apply diagnostic labels to ABR data using reference-based indicators such as pea...
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This study investigates the application of advanced fine-tuned Large Language Models (LLMs) for Turkish Sentiment Analysis (SA), focusing on e-commerce product reviews. Our research utilizes four open-source Turkish S...
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This study presents the development of a mobile application for classifying skin conditions into Melanoma, Acne, and Healthy skin. A dataset of 214 Melanoma images from Dermnet, 395 Acne images, 400 Healthy skin image...
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Colorectal intraepithelial neoplasia is a precancerous lesion of colorectal cancer, which is mainly diagnosed using pathological images. According to the characteristics of lesions, precancerous lesions can be classif...
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Federated Learning (FL) is a promising privacy-preserving distributed machine learning paradigm. However, data privacy leakage and Byzantine clients are common challenges in the FL aggregation phase. While extensive r...
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