Abstract: Breast cancer is a highly complex disease that requires precise molecular subtyping to guide tailored treatment strategies. In this study, we employed a marker-based watershed segmentation ...

Abstract: Face authentication (FA) schemes are universally adopted. However, current FA systems are mainly camera-based and susceptible to masks and vulnerable to spoofing attacks. This paper exploits ...

Abstract: Relic landslides, formed over a long period, possess the potential for reactivation, making them a hazardous geological phenomenon. While reliable relic landslide detection benefits the ...

Abstract: In the field of medical imaging, correct instance segmentation is essential. This work attempts to address the problems related to renal micro-structure segmentation by using the power of ...

Abstract: Image inpainting is a technique designed to remove unwanted regions from images and restore them. This technique is expected to be applied in various applications, including image editing, ...

Abstract: Reconfigurable intelligent surfaces (RISs) are an emerging technology for improving spectral efficiency and reducing power consumption in future wireless systems. This paper investigates the ...

Abstract: Electroencephalography (EEG) is an effective assessment tool to identify autism spectrum disorders with low cost, and deep learning has been applied in EEG analysis for extracting meaningful ...

Abstract: This research suggests a strong framework for automated malaria detection using a Convolutional Neural Network (CNN) model. The dataset, sourced from Kaggle, consists of 27,558 ...

Abstract: Face Recognition is a computer vision technology that identifies or verifies a person’s identity using a person’s facial features. It is widely used in different fields like security, ...

Abstract: Eggplant (Solanum melongena L.) is a widely cultivated vegetable in the Philippines, where accurate size grading plays a crucial role in determining market ...