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Currently, technical problems regarding the electronic transmission of large image data sets have essentially been solved.
An algorithm is presented in this paper to facilitate the exploration of large image collections based on visual similarities.
This approach enables the annotation of large image databases at the bounding box level in a short time.
We provide an original mesh lattice framework which is more convenient for structural representations of large image data by means of interest point sets and their morphological analysis.
Three alternatives of pLSA-based models that provided in [13] were presented by using asymmetric learning for semantic indexing of large image collections.
Texture-based scribble boosting greatly facilitates the colorization of large image regions of uniform texture which are expected to obtain common chrominance.
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The exhibition also includes a series of large images of nudes on the beach, notable for the way in which the monumental bodies of the figures fuse with the sand.
The cross-correlation uses a parallelized FFT-method to accelerate the processing of large images.
This paper presents a texture synthesis algorithm that was designed for the tile-less generation of large images of arbitrary size from small sample images.
HiRISE has acquired hundreds of large images of past, present and potential future landing sites and has contributed to scientific and engineering studies of those sites.
The originality of this architecture allows for a scalable and a totally embedded on Chip FPGA for the processing of large images.
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Justyna Jupowicz-Kozak
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