Abstract: Applications like disaster management, urban planning, and environmental monitoring rely on satellite image categorization. This project develops a machine learning pipeline using ...
Abstract: Medical image segmentation remains a challenging task due to the intricate nature of anatomical structures and the wide range of target sizes. In this paper, we propose a novel U-shaped ...
Abstract: Simultaneous localization and mapping (SLAM) enables robots to localize in uncertain environments and has been widely used in the field of robotics. However, traditional vision SLAM systems ...
Abstract: Data annotation in medical image segmentation is time-consuming and expensive. Semi-supervised learning (SSL) presents a viable solution. However, unlike organ segmentation, current ...
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: The fast growth of internet and communications networks has drastically enhanced data transport, allowing tasks like Speech Emotion Recognition (SER), an essential aspect of human-computer ...
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 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: The integrated Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) system has been widely used in vehicular positioning and navigation. However, the complex ...
Abstract: This study proposes a robust and efficient two-stage deep learning framework aimed at the accurate classification of Chest X-ray images into NORMAL and PNEUMONIA categories. The methodology ...
Abstract: The shape and size of the placenta are closely related to fetal development in the second and third trimesters of pregnancy. Accurately segmenting the placental contour in ultrasound images ...
Abstract: Intrusion Detection Systems (IDS) are critical components in securing network environments against a myriad of cyber threats. The evolution of machine learning (ML) techniques has ...