Hong-zhang Wei,,Rui-ming Jia.Scale-invariant globalsparse image matching method based on Delaunay trian-gle. Automatic Target Recognition and Image Analysis.Proc.SPIE . 2009Hong-zhang Wei,Rui-ming Jia. Scale-invariant global sparse image matching method based on Delaunay triangle,Automatic Target ...
Scale-invariant sparse PCA on high-dimensional meta-elliptical data. Journal of the American Statistical Association, 109(505):275-287, 2014.Han and Liu, 2014] Han, F. and Liu, H. (2014). Scale-invariant sparse PCA on high-dimensional meta- elliptical data. Journal of the American ...
Receptive field (RF) size and preferred spatial frequency (SF) vary greatly across the primary visual cortex (V1), increasing in a scale invariant fashion with eccentricity. Recent studies reveal that preferred SF also forms a fine-scale periodic map. A
Key points are scale-invariant points in images. Also, the key points are the visual patterns/clues in each image, thereby capturing sparse interesting regions in the image, which is beneficial in dealing with inter-class similarity and sparsity problems to some extent. These key points and ...
DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures - yanghr/DeepHoyer
To express them in generalized scale-invariant terms, limiting amounts of energy/matter in some form (resources/substrates) and a strong and increasing demand for energy/matter in some form (products) create a "gradient" and a potential for the emergence of intense flux of energy/matter ...
To make the network invariant to absolute intensities we also shift the intensities of each MR channel c of every training segment by ic=rcσc. rc is sampled for every segment from N(0,0.1) and σc is the standard deviation of intensities under the brain mask in the corresponding image....
However, some existing methods focus too much on the shape and volume of the hippocampus rather than its spatial information, and the extracted information is independent of each other, ignoring the correlation between local and global features. In addition, many methods cannot be effectively applied...
(SVM) classifier to detect vehicles within UAV imagery, achieving improved detection under diverse lighting conditions, albeit at a relatively slower inference speed. Moranduzzo et al.18utilized SVM to categorize the Scale-Invariant Feature Transform (SIFT) keypoints in UAV images into vehicle and ...
8 Scale-Invariant Image Descriptors for Matching In the following, we shall combine the above mentioned generalized scale-space interest points with local image descriptors. For each interest point, we will compute a complementary image descriptor in analogous ways as done in the SIFT and SURF opera...