Results 111 to 120 of about 75,969 (161)

MidFusionEfficientV2: Improving Ophthalmic Diagnosis with Mid-Level RGB-LBP Fusion and SE Attention. [PDF]

J Clin Med
Keles JK, Kiziloluk S, Sert E, Talo F, Yildirim M.   +4 more
europepmc   +1 more source

LeafFusionNet: a hybrid deep learning approach for robust plant disease detection. [PDF]

Front Artif Intell
Das S, Prethija G, Sudha C.
europepmc   +1 more source

Bio-optimized complex valued spatiotemporal GNN for herbal species classification. [PDF]

Sci Rep
Vats P, Vats S, Sharma A, Yadav SL, Chaudhary D.   +4 more
europepmc   +1 more source

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Texture classification using texture spectrum

Pattern Recognition, 1990
Abstract Pursuing our previous study where the Texture Spectrum method has been proposed for texture analysis, the purpose of this paper is to demonstrate the usefulness of the Texture Spectrum for texture classification. Promising results are obtained when applying the Texture Spectrum to classify four of Brodatz's natural images.
Dong-Chen He
exaly   +2 more sources

Compact color–texture description for texture classification

Pattern Recognition Letters, 2015
We show that combining multiple texture description methods significantly improves the performance compared to using the single best texture method alone.We further propose to use information theoretic compression approach to compress high-dimensional multi-texture features into a compact heterogeneous texture representation.We perform a comprehensive ...
Jorma Laaksonen, Fahad Shahbaz Khan, Michael Felsberg   +2 more
exaly   +3 more sources

Measuring texture classification algorithms

Pattern Recognition Letters, 1997
Summary: The texture analysis literature lacks a widely accepted method for comparing algorithms. This paper proposes a framework for comparing texture classification algorithms. The framework consists of several suites of texture classification problems, a standard functionality for algorithms, and a method for computing a score for each algorithm. We
Smith G., Burns I.
exaly   +4 more sources

Texture classification using fuzzy uncertainty texture spectrum

Neurocomputing, 1998
Abstract A new method using fuzzy uncertainty, which measures the uncertainty of the uniform surface in an image, is proposed for texture analysis. A grey-scale image can be transformed into a fuzzy image by the uncertainty definition. The distribution of the membership in a measured fuzzy image, denoted by the fuzzy uncertainty texture spectrum ...
Yih-Gong Lee, Jia-Hong Lee, Yuang-Cheh Hsueh   +2 more
exaly   +2 more sources

On texture classification

International Journal of Systems Science, 1997
Texture analysis has found wide application in, say, remote sensing, medical diagnosis, and quality control.
Chen, Y.Q., Nixon, M.S., Thomas, D.W.
openaire   +1 more source

Wavelet based texture classification

Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002
Texture are one of the basic features in visual searching and computational vision. In the literature most of the attention has been focussed on the texture features with minimal consideration of the noise models. In this paper, we investigate the problem of texture classification from a maximum likelihood perspective.
Sebe, Niculae, M. S. Lew
openaire   +2 more sources