Convolutional neural network (CNN) has been widely applied in hyperspectral image (HSI) classification exhibiting excellent performance. Weak generalization of CNN models to different datasets is a common issue in this domain largely because of …
Clustering algorithms play an essential and unique role in classification tasks, especially when annotated data are unavailable or very scarce. Current clustering approaches in remote sensing are mostly designed for a single data source, such as …
Recent progress in spectral classification is largely attributed to the use of convolutional neural networks (CNN). While a variety of successful architectures have been proposed, they all extract spectral features from various portions of adjacent …
In this paper we develop a novel classification method for multibeam sonar images based on the Weyl transform. The texture descriptor based on Weyl coefficients describes effectively the multiscale correlation features appearing in the sonar images. …
Hyperspectral imagery contains a wealth of spectral and spatial information that can improve target detection and recognition performance. Conventional feature extraction methods cannot fully exploit both spectral and spatial information. Data fusion …
Nowadays, we have diverse sensor technologies and image processing algorithms that allow one to measure different aspects of objects on the Earth [e.g., spectral characteristics in hyperspectral images (HSIs), height in light detection and ranging …
The 2013 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC) of the IEEE Geoscience and Remote Sensing Society aimed at investigating the synergistic use of hyperspectral and Light Detection And Ranging (LiDAR) data. The data …
We propose a novel semisupervised local discriminant analysis method for feature extraction in hyperspectral remote sensing imagery, with improved performance in both ill-posed and poor-posed conditions. The proposed method combines unsupervised …
Vehicle tracking is of great importance for tunnel safety. To detect incidents or disturbances in traffic flow it is necessary to reliably track vehicles in real-time. The tracking is a challenging task due to poor lighting conditions in tunnels and …
We propose a novel semi-supervised local discriminant analysis (SELD) method for feature extraction in hyperspectral remote sensing imagery. The proposed method combines a supervised method (Linear Discriminant Analysis (LDA)) and an unsupervised …