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The workshop will mark the last of the ImageNet Challenge competitions, and focus on unanswered questions and directions for the future. The workshop will 1) present current results on the challenge c...
Scaling up machine-learning (ML), data mining (DM) and reasoning algorithms from Artificial Intelligence (AI) for massive datasets is a major technical challenge in the time of "Big Data". The past te...
Over the past few decades, human recognition has been extensively studied. Most of the research concentrates on typical physiological traits, e.g., face, fingerprint, voice, etc., which are usually di...
Static analysis techniques that represent program states as formulas typically generate a large number of redundant formulas that are incrementally constructed from previous formulas. In addition to q...
Machine learning and statistics with very large datasets is now a topic of widespread interest, both in academia and industry. Many such tasks can be posed as convex optimization problems, so algorith...
Many technical aspects are involved in the upgrading of satellite image databases: geometric registration, resampling, radiometric adjustment, mosaicking. In this paper, after an overview of all prob...
Handling Large Terrain Data in Gis     Database  Large  DEM/DTM       2015/7/7
This paper presents a research and development project that will provide an extension to 2D geo-databases for handling large terrain data. It first discusses application requirements and system desig...
The objective of this paper is to show the way multiple source data like aerial photos, maps and descriptive information are combined and amalgamated to form an Internet or Intranet application. The ...
Designers often seek modular architectures to better accommodate expected changes and to enable parallel development. However, we lack a formal theory and model of modularity and software evolution, w...
Long number multiplications (n ≥ 128-bit) are a primitive in most cryptosystems. They can be performed better by using Karatsuba-Ofman technique. This algorithm is easy to parallelize on workstatio...
The major challenges that sign language recognition (SLR) now faces are developing methods that solve largevocabulary continuous sign problems. In this paper, transitionmovement models (TMMs) are pro...
Up to now, the major problem for large vocabulary sign language recognition lies in the huge search space due to a variety of recognition classes.Analytical methods such as Dynamic Time Wrapping (DTW...
This paper has put forward a new architecture classifier method for Chinese sign language recognition (CSLR) to improve the performance of recognition. It is a signer-independent method, to recognize ...
The major challenges that sign language recognition (SLR) now faces are developing methods that solve large vocabulary continuous sign problems. In this paper, large vocabulary continuous SLR based on...

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