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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…

This study evaluates the performance of Faster R-CNN and YOLOv7 object detectors for dynamic ship detection in maritime applications. Both algorithms are tested under challenging conditions, including poor image quality due to cloud and dust obscuration, varyi…

The uncontrolled spread of forest fires, driven by climate change and increasing human activities, poses a significant global challenge, disrupting the delicate balance of ecosystems. These fires, whether caused by natural disasters or human factors, have seve…

Bu çalışmada, 596 kayıt ve 31 sütundan oluşan veri setiyle R programlama dili üzerinde akciğer kanserinin ikili sınıflama başarısı test edilmiştir. İlk aşama veri setinin temizlemesi, boş değerlerin kaldırılması ve verilerin denetlenmesinden oluşmaktadır. Daha…

Bu çalışmada UCI Makine Öğrenmesi havuzundan alınan kardiotokogram verisinde morfolojik örüntü sınıflandırması yapılmıştır. Sınıflandırıcı olarak kompleks değerli yapay sinir ağları kullanılmıştır. Sınıflandırıcının performansı 10-katlı çapraz doğrulama yaklaş…

Hyperspectral images offer a good separability among land cover classes, owing to their advantages to provide spectral bands with narrow wavelength intervals. It is also possible to further increase classification accuracy of hyperspectral images by integrat…

Deep learning allows computational models of multiple processing layers to learn and represent data with multiple levels of abstraction mimicking how the brain perceives and understands multimodal information, thus implicitly capturing intricate structures of …

Open-finance systems increasingly compose portfolio models, data services, and execution interfaces supplied by different parties. This modularity is useful only if the executed wealth path can be checked independently of the model that proposed it. We study a…

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…

Quality control in the industry is becoming increasingly important as a result of increasing market competition and the need for quality products. The increasing complexity of industrial processes and the increase in the amount of data available have promoted …

E-commerce is evolving rapidly, creating a more competitive market environment. With this development, gaining a competitive advantage has become even more crucial. Companies implement various strategic moves to maintain their position in this competitive mark…

The main goal of this research is to investigate the potential and current role of generative AI in improving and developing avionics systems, and aviation-related applications. Avionics, a vital part of aviation industry, consists of a set of equipment and el…

Forecasting earthquakes is challenging due to the difficulty in detecting underground phenomena. However, statistically, 30% of large earthquake foreshocks occur before the main shock, which indicates that, theoretically, it is possible to forecast them. Howev…

In the last decade, deep learning in general and Convolutional Neural Networks (CNN) have achieved a human level and outstanding performance in almost all computer-based systems such as classification(text, images, and videos). Building an efficient CNN archit…

Complex-valued artificial neural network (CVANN) has been developed to process data with complex numbers directly. In a CVANN the weights, threshold, inputs and outputs are all complex numbers. The convergence of the CVANN back propagation algorithm depending …

It is important to determine the initial level of failures of induction motors used in many industrial applications. The sudden stops of the system can be prevented with the pre-detection of the fault. The experiment mechanism was established to detect mechani…

 In today's applications, a significant increase in the use of deep learning algorithms is noticeable. The convolution neural network (CNN) of deep learning has been used frequently recently, especially for the successful discrimination of people and vehicles …

In this paper we presents an application of deep learning techniques to recognize handwritten source code characters. Although there are many works on the handwritten character recognition (HCR) problem, very few works have been done about the offline handwrit…

Neural Network has been used in a number of scientific fields including medical diagnosis. It is clear that classification is one of the main challenges in any medical diagnosis. However, the drawbacks of conventional neural network classifier are summarized a…

The Motion Picture Association of America(MPAA) is used in the United States to rate a film's compatibility via its content. These systems evaluate ratings according to the scenes in the movies. In this work, a deep learning based classification technique is p…