Abstract: The goal is to improve the navigation safety of a semi-autonomous aquatic robot using computer vision and deep learning techniques. Three main approaches were evaluated: object detection ...

Abstract: Water scarcity along with poor management of water sources is turning to be a matter of global concern, and this calls for an intelligent monitoring system. This paper introduces a new ...

Abstract: Deep vein thrombosis (DVT) is a prevalent medical condition. For pulmonary embolism to prevent potentially fatal acute consequences, an accurate identification of deep vein thrombosis is ...

Abstract: Human trafficking is a serious problem that requires new ideas and data-driven approaches to identify and solve. In this study, we analyze large datasets to identify patterns and anomalies ...

Abstract: Credit card fraud detection remains a critical challenge in the financial industry, demanding robust, scalable, and adaptive solutions. This paper explores the existing research landscape, ...

Abstract: Tumor segmentation is crucial for surgical planning and precise tumor resection for effective treatment. Traditionally, tumor localization has been performed using medical imaging techniques ...

Abstract: Glaucoma, a leading cause of irreversible blindness, requires precise segmentation of the optic disc and optic cup in fundus images for early diagnosis and progression monitoring. This study ...

Abstract: The success of deep learning in 3D medical image segmentation hinges on training with a large dataset of fully annotated 3D volumes, which are difficult and time-consuming to acquire.

Abstract: The poultry industry has been driven primarily by broiler chicken production and has grown into the world’s largest animal protein sector. Automated detection of chicken carcasses on ...

Abstract: Understanding surgical scenes can provide better healthcare quality for patients, especially with the vast amount of video data that is generated during MIS. Processing these videos ...