Abstract: This paper introduces an innovative content-based image retrieval system for precise and effective retrieval of satellite images. The system integrates liquid autoencoders with shearlet ...
Abstract: This research focuses on developing a complex framework for automatic diagnosis purposes of Alzheimer's disease from MRI brain data, with emphasis placed on advancement in accuracy towards ...
Abstract: This study proposed a method that integrates multi-view image processing, depth estimation, and point cloud generation to accurately reconstruct a 3D model of a rail. The method is tested by ...
Recently developed quantum computers support mid-circuit measurements, allowing qubit measurement, resetting, and reuse during the execution of quantum circuits. This capability opens new ...
Abstract: Semi-supervised learning (SSL) has achieved remarkable progress in the field of medical image segmentation (MIS), but it still faces two main challenges. First, the consistency learning ...
Abstract: In recent years, there has been an increasing interest in the aesthetics of teeth, particularly regarding tooth color. Among the various approaches to improve the appearance of teeth, crown ...
Abstract: Image captioning is an emerging field at the intersection of computer vision and natural language processing (NLP). It has shown great potential to enhance accessibility by automatically ...
Abstract: Computational resources, which presents a significant challenge in resourceconstrained environments, particularly in developing countries. Consequently, the development of decoding ...
Abstract: With the ease of classifying land through satellite imaging, remote sensing has captured the Earth observation domain. Traditional methods for analyzing satellite images relied on manual ...
Abstract: Weeds are problems for crop yields because they exert harmful effects on the yields by competing with cultivated crops for necessary resources like nutrients, sunlight, and soil. As a result ...
Abstract: Human cognition is robust in estimating depth ordering and occluded regions of objects, including amodal instance segmentation (AIS). Object-centric representation learning (OCRL) is an ...
Abstract: Semantic segmentation is critical in remote sensing applications such as urban planning, disaster management, and environmental monitoring. However, segmenting complex satellite images ...
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