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BAY 43-9006 Exhibits Broad Spectrum Oral Antitumor Activity and Targets the RAF/MEK/ERK Pathway and Receptor Tyrosine Kinases Involved in Tumor Progression and Angiogenesis
The RAS/RAF signaling pathway is an important mediator of tumor cell proliferation and angiogenesis. The novel bi-aryl urea BAY 43-9006 is a potent inhibitor of Raf-1, a member of the RAF/MEK/ERKExpand
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Sorafenib blocks the RAF/MEK/ERK pathway, inhibits tumor angiogenesis, and induces tumor cell apoptosis in hepatocellular carcinoma model PLC/PRF/5.
Angiogenesis and signaling through the RAF/mitogen-activated protein/extracellular signal-regulated kinase (ERK) kinase (MEK)/ERK cascade have been reported to play important roles in the developmentExpand
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Median Robust Extended Local Binary Pattern for Texture Classification
We introduce a novel descriptor for texture classification, the median robust extended LBP (MRELBP). Expand
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BRINT: Binary Rotation Invariant and Noise Tolerant Texture Classification
We propose a simple, efficient, yet robust multiresolution approach to texture classification-binary rotation invariant and noise tolerant (BRINT). Expand
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Texture Classification from Random Features
  • Li Liu, P. Fieguth
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine…
  • 1 March 2012
Inspired by theories of sparse representation and compressed sensing, this paper presents a novel approach for texture classification based on random projection, suitable for large texture database applications. Expand
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Extended local binary patterns for texture classification
This paper presents a novel approach for texture classification, generalizing the well-known local binary pattern (LBP) approach. Expand
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An Adaptive and Fast CFAR Algorithm Based on Automatic Censoring for Target Detection in High-Resolution SAR Images
An adaptive and fast constant false alarm rate (CFAR) algorithm based on automatic censoring (AC) is proposed for target detection in high-resolution synthetic aperture radar images. Expand
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Sorted random projections for robust rotation-invariant texture classification
This paper presents a simple, novel, yet very powerful approach for robust rotation-invariant texture classification based on random projection. Expand
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Local binary features for texture classification: Taxonomy and experimental study
We perform a large scale performance evaluation for texture classification, empirically assessing forty texture features including thirty two recent most promising LBP variants and eight non-LBP descriptors based on deep convolutional networks on thirteen widely-used texture datasets. Expand
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Sorted Random Projections for robust texture classification
This paper presents a simple and highly effective system for robust texture classification, based on (1) random local features, (2) a simple global Bag-of-Words (BoW) representation, and (3) Support Vector Machines (SVMs) based classification. Expand
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