For people, matching what they see on the ground to a map is second nature. For computers, it has been a major challenge. A ...
Abstract: This research focuses on generating image captions using Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models. As deep learning advances, the availability of large ...
Abstract: In recent years, convolutional neural networks (CNNs) have been impressive due to their excellent feature representation abilities, but it is difficult to learn long-distance spatial ...
Abstract: Remote sensing scene classification is a vital task in remote sensing image analysis with significant application potential. In recent years, convolutional neural network (CNN)-based methods ...
Abstract: The segmentation of ultra-high resolution images poses challenges such as loss of spatial information or computational inefficiency. In this work, a novel approach that combines ...
Abstract: This paper presents a comprehensive comparison of Convolutional Neural Network (CNN) and Quantum Convolutional Neural Network (QCNN) in cloud-based environments, focusing on training ...
Abstract: Kidney cancer is a commonly diagnosed cancer disease in recent years, and Renal Cell Carcinoma (RCC) is the most common kidney cancer responsible for 80% to 85% of all renal tumors. The ...