Throughout the scientific computing space, deep learning algorithms have shown excellent
performance in a wide range of applications. As these deep neural networks (DNNs) …

This paper presents a comprehensive study of robotic manipulation tasks, focusing on the
movement planning and task-handling capabilities of robots. We introduce a novel approach …

Deep learning has proven to be an immensely powerful tool within the remote sensing
space, with capabilities to perform tasks like classification, object detection, and …

Deep convolutional neural networks (DCNNs) have shown excellent performance in object
detection tasks over the last five years. The widespread adoption of DCNNs in computer …

Within computer vision, deep neural networks (DNNs) have gained tremendous popularity in
recent years due to their ability to extract and classify visual features. As this technology has …

Deep neural network (DNN) algorithms have increased dramatically across a wide variety of
remote sensing applications. However, as computer vision (CV) researchers have utilized …

Mathematical morphology has been explored in deep learning architectures, as a substitute
to convolution, for problems like pattern recognition and object detection. One major …

Recently, computer vision tasks such as classification and object detection have been
dominated by deep neural net-work (DNN) approaches. As DNN methodologies have …