Fine-grained categorization refers to the task of classifying objects that belong to the same basic-level class (e.g. different bird species) and share similar shape or visual app...
Having effective methods to access the images with desired object is essential nowadays with the availability of huge amount of digital images. We propose a semantic higher-level ...
Ismail Elsayad, Jean Martinet, Thierry Urruty, Cha...
Due to the presence of speckle, segmentation of SAR images is generally acknowledged as a difficult problem. A large effort has been done in order to cope with the influence of sp...
The data model for image representation in terms of projective Fourier transform (PFT) is well adapted to both image perspective transformations and the retinotopic mappings of th...
In this paper, we present a novel image representation that renders it possible to access natural scenes by local semantic description. Our work is motivated by the continuing effo...
This paper is concerned with the derivation of a progression of shadow-free image representations. First, we show that adopting certain assumptions about lights and cameras leads t...
Graham D. Finlayson, Steven D. Hordley, Cheng Lu, ...
Conventional SVM-based image coding methods are founded on independently restricting the distortion in every image coefficient at some particular image representation. Geometrical...
Gustavo Camps-Valls, Juan Gutierrez, Gabriel G&oac...
Building robust low and mid-level image representations, beyond edge primitives, is a long-standing goal in vision. Many existing feature detectors spatially pool edge information...
Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylo...
This paper reports on a new approach for visualizing multi-field MRI or CT datasets in an immersive environment with medical applications. Multi-field datasets combine multiple sc...
ABSTRACT: OCR is an error-prone process. It is time-consuming and expensive to manually proofread OCR results. The errors remaining in OCRed texts can cause serious problems in rea...