Co-occurrence pattern
Local Tri directional Weber Rhombus Co occurrence Pattern: A New Texture Descriptor for Brodatz Texture Image Retrieval
... the pattern based techniques like LBP, Local ternary patterns (LTP), Center symmetric local binary patterns (CSLBP) encodes the difference of pixels to obtain local information structure but ignores the original ...
5
An effective image retrieval based on optimized genetic algorithm utilized a novel SVM-based convolutional neural network classifier
... metric co-occurrence pattern; LDOP: local directional order pattern; CCF + BPF: color cooccurrence feature + bit pattern feature; GP: genetic programming; CBIR: content-based image ...
29
Improved Neural Network based Multi label Classification with Better Initialization Leveraging Label Co occurrence
... label co-occurrence ...each co-occurrence pattern before back- propagation, some overlapped co-occurrences might be explained by the superset or combination of sub- sets after ...
6
COPE: Interactive Exploration of Co-occurrence Patterns in Spatial Time Series.
... (Co-Occurrence Pattern Exploration), which allows users to extract events of interest from data and detect various co-occurrence patterns among ...
15
An Empirical Study of the Occurrence and Co-Occurrence of Named Entities in Natural Language Corpora
... of occurrence and co-occurrence of NEs in standard large English news corpora - providing valuable insight for the understanding of the corpus, and subsequently paving way for the development of ...
8
QUANTIFYING AND ANALYSING MAIZE SEED VARIETY USING IMAGE PROCESSING
... The paper is proposed to present a review of seed technology, seed germination and vigor methods using image processing. Computer–aided image analysis techniques have been recently developed in monit oring seed growth ...
6
Strong evidence that the common variant S384F in BRCA2has no pathogenic relevance in hereditary breast cancer
... 43 and 57 years of age). One woman with bilateral breast cancer (diagnosed at ages 32 and 50) did not carry the variant. Both tumours were heterozygous for the S384F variant, so loss of the wild-type allele could be ...
5
A hybrid framework for brain TUMOR detection and classification using neural network
... the calculation of these features. Texture features provide specific information about the distribution of various gray levels in an image. The texture features calculated are standard deviation, variance, mean, ...
6
AlikE Content Detection in Image and Video
... Feature extraction explains the relevant shape information contained in an image so that the task of arranging the image is made easy by a simple procedure [15]. In video processing and in image processing, feature ...
6
Associating expression and genomic data using co-occurrence measures
... proposed co-occurrence ...the co-occurrence between this associations and expression regimes/mutation data/ copy number data of other ...
14
Quaternion Representation Based Particle Swarm Optimization Classifier For Handwritten Kannada Numerals Recognition
... Binary Pattern (ALBP) and Gray-Level Co-occurrence Matrix (GLCM) are suitable features to extract the texture features from preprocessed numeral ...
14
Grinding surface roughness measurement based on the co occurrence matrix of speckle pattern texture
... speckle pattern and investigate the influence of the distance L variations on surface roughness evalua- ...speckle pattern images from stan- dard grinding surface roughness specimens are ob- ...speckle ...
9
The Co planarity and Symmetry Principle of Earthquake Occurrence
... This study allowed existence of the errors, but those er- rors do not interfere the co-planarity and the symmetry principle. Errors may come from the inaccuracy of ob- servation time, perhaps the errors accelerate ...
6
Utilizing Co Occurrence of Answers in Question Answering
... What kind of relations between questions could be utilized is a key problem in building the batch QA system. By observing the test ques- tions of TREC QA, we found that the questions given under the same topic are not ...
8
PhonMatrix: Visualizing co occurrence constraints of sounds
... The basic idea of Sukhotin’s algorithm is that vowels and consonants have the tendency not to occur in groups within words but to alternate. Based on the additional assumption that the most frequent symbol in the text is ...
6
Multi-View Information-Theoretic Co-Clustering for Co-Occurrence Data
... of co-occurring matrices (rows for samples and columns for features) can be viewed as the frequency or counts of a certain feature occurred in a certain ...the co-occurrence analysis is ...
8
Kernel Sparse Coding & Texture Feature based Segmentation for Cerebral Edema
... - OCCURRENCE M ATRIX (GLCM): The Gray Level co-occurrence matrix is used for weighing the image which has been converted into gray image will be weighed by this and it will give the results in the ...
5
Automatic Approaches for Gene Drug Interaction Extraction from Biomedical Text: Corpus and Comparative Evaluation
... Adding patterns with more diversity in al- lowed parts of speech in series of interaction terms that connect genes and drugs in interactions can improve recall performance. A review of parts of speech (POS) in missed ...
9
Euclidean Embedding of Co-occurrence Data
... Embedding algorithms search for a low dimensional continuous representation of data, but most algorithms only handle objects of a single type for which pairwise distances are specified. This paper describes a method for ...
31
Age Classification with Co-Occurrence Features on LBP Based Texton Matrix
... ABSTRACT: Age classification from facial images is increasingly receiving attention in computer vision applications. To address this classification problem, the present paper proposes a method, computes the local binary ...
6