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 this domain largely because limited amount labeled training samples. In article, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xli...

Feature selective cells in the primary visual cortex of several species are organized in hierarchical topographic maps of stimulus features like "position in visual space", "orientation" and" ocular dominance". In order to understand and describe their spatial structure and their development, we investigate a self-organizing neural network model based on the feature map algorithm. The model exp...

A novel scheme for texture segmentation is presented. Our algorithm is based on generalizing the intensity-based geodesic active contours model to the Gabor spatial-feature space of images. First, we apply the Gabor-Morlet transform to the image using self similar Gabor functions, and then implement the geodesic active snakes mechanism in this space. The spatial-feature space is represented, vi...

This paper proposes a geodesic-distance-based feature that encodes global information for improved video segmentation algorithms. The feature is a joint histogram of intensity and geodesic distances, where the geodesic distances are computed as the shortest paths between superpixels via their boundaries. We also incorporate adaptive voting weights and spatial pyramid configurations to include s...

Studies of visual search with patients with spatial attentional deficits have shown that the ability to bind basic features properly and thus to search for the conjunction of two spatially contiguous features is compromised. However, the effect of spatial deficits on feature search is more controversial. Here, we explore questions raised by the neuropsychological literature regarding feature pr...

Hyperspectral imagery contains a wealth of spectral and spatial information that can improve target detection and recognition performance. Typically, spectral information is inferred pixel-based, while spatial information related to texture, context and geometry are deduced on a per-object basis. Existing feature extraction methods cannot fully utilize both the spectral and spatial information....

Video hashing is a common solution for content-based video retrieval by encoding high-dimensional feature vectors into short binary codes. Videos not only have spatial structure inside each frame but also have temporal correlation structure between frames, while the latter has been largely neglected by many existing methods. Therefore, in this paper we propose to perform video hashing by incorp...