[PDF] Top 20 A New Method of Voiced/Unvoiced Classification Based on Clustering
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A New Method of Voiced/Unvoiced Classification Based on Clustering
... extracted based on the peak value in the cepstral domain by using different ...cepstral method has other deficien- cies. It means that for some voiced frames, although there is a distinguishable peak ... See full document
12
Voiced/Unvoiced Classification by Hybrid Method Based On Cepstrum and EMD
... a new statistical voiced/unvoiced ...this method voicing decision are made using multi feature voiced unvoiced classification based on statistical analysis of ... See full document
6
A Review on Clustering Analysis based on Optimization Algorithm for Datamining
... of clustering. The clustering is one of the problem in data mining that always affected many ...researchers. Clustering is one of the important unsupervised classification ...the new ... See full document
6
Proposing a Novel Cost Sensitive Imbalanced Classification Method based on Hybrid of New Fuzzy Cost Assigning Approaches, Fuzzy Clustering and Evolutionary Algorithms
... Even in the cases that there are clear boundaries among the labeled data of different classes, data in the same class still has some characteristics representing its degree of proximity to the class boundaries. It is ... See full document
9
A NEW APPROACH FOR IMAGE FEATURE VECTOR CLASSIFICATION USING UNSUPERVISED CLUSTERING METHOD
... a New Fuzzy Cluster Centroid (NFCC) for unsupervised classification algorithm to improve the traditional FCM and fuzzy weighted c means (FWCM) ...the new term reduces the number of iterations for ... See full document
10
A NEW CLUSTERING-BASED APPROACH FOR MODELING FUZZY RULE-BASED CLASSIFICATION SYSTEMS
... a new clustering-based method for modeling accurate fuzzy rule based classification ...mapping method was utilized to compute a new representation of ...this ... See full document
11
Local binary patterns for 1-D signal processing
... a new 1-dimensional local binary pattern (LBP) signal processing method is pre- ...LBP based speech processing is demonstrated on two signal processing problems: - (i) signal segmentation and (ii) ... See full document
5
Advances in Nonparametric Bayesian Methods for Clustering and Classification.
... both clustering and classification via discrimi- nant ...for classification and clustering purposes (Jackson et ...the classification of the programs, the proposed method fits ... See full document
94
A New Unsupervised Clustering based Feature Extraction Method
... 2: Classification accuracy on Sonar Data set For each experiment, 12 of these sets are used as training data, while the 13th is reserved for ...shows classification accuracy for different number of ... See full document
7
Adaptive V/UV Speech Detection Based on Characterization of Background Noise
... decision method for noisy speech is proposed. The paper presents a method for estimating the probability density function of correlation peak values and also estimating the optimal threshold of the V/UV ... See full document
12
A Survey on Classification and Clustering of Images Using Evolutionary Techniques
... With the advancement in technology digital images can be processed using various algorithms. An image can be a line art (called Vector graphics) or pixel based (called bitmaps) that may be used to provide a visual ... See full document
7
In-line recognition of agglomerated pharmaceutical pellets with density-based clustering and convolutional neural network
... 0.05, the CNN classifier achieved 0.92 true positive rate (threshold 0.46), while the area-based classifier achieved 0.70 true positive rate (area threshold 4.0A, A – area of a single pellet). Note that high area ... See full document
6
A new clustering routing method based on PECE for WSN
... algorithm based on clustering than using the plane routing algorithm ...[4]. Clustering al- gorithm is to divide the sensor network nodes into dif- ferent ...of clustering algo- rithm to ... See full document
13
A new classification of glaucomas
... this classification and after spending enough time to place a new case in the group of ACG or OAG, one may expect to receive help in therapeutic decision ...a new level of analysis, this time a ... See full document
17
AN ITERATIVE GENETIC ALGORITHM BASED SOURCE CODE PLAGIARISM DETECTION APPROACH USING NCRR SIMILARITY MEASURE
... the clustering algorithm often used in traffic management for laboratory risk prediction ...through classification algorithm finds an area where traffic accidents often happen to share the thinking type, or ... See full document
10
A new genetic algorithm based clustering for binary and imbalanced class data sets
... of clustering for categorical data has not grown as tremendously as that for numerical ...of clustering for categorical data being not as clear as the problem for numerical data [Duda and Hart, ...make ... See full document
36
A new method for cancer detection based on diffusion reflection measurements of targeted gold nanorods
... a new method for cancer detection based on diffusion reflec- tion ...This method enables discrimination between cancerous and noncancerous tissues due to the intense light absorption of gold ... See full document
7
A Compression Method for PML Document Based on Internet of Things
... Obviously the Lossy compression is not out cake because the PML data such as EPC tag needs to be accurate to identify the object after decompression. Among the lossless compression techniques like LZW (Lempel-Ziv-Welch) ... See full document
6
Robust and Efficient Segmentation of Blood Vessel in Retinal Images using Gray-Level Textures Features and Fuzzy SVM
... The SVM has been widely used in pattern recognition applications due to its computational efficiency and good generalization performance. It is widely used in object detection and recognition, content-based image ... See full document
10
A New Parametric Estimation Method for Graph based Clustering
... spectral clustering can be interpreted as trying to find a partition of the graph such that the random walk stays long within the same cluster and seldom jumps between clusters (von Luxburg, ...Markov ... See full document
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