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This paper mainly discussed the process to classify Anthracnose and Downey Mildew, watermelon leaf diseases using neural network analysis. A few of infected leaf samples were collected and they were captured using a digital camera with specific calibration procedure under controlled environment. The classification on the watermelon's leaf diseases is based on color feature extraction from RGB color...
In this paper, we propose a new sequential multitask pattern recognition model called Resource Allocating Network for Multi-Task Learning with Metric Learning (RAN-MTLML). RAN-MTLML has the following five functions: one-pass incremental learning, task-change detection, memory/retrieval of task knowledge, reorganization of classifier, and knowledge transfer. The knowledge transfer is actualized by...
The work presented in this paper proposes a new approach of using subspace grids for recognizing patterns in multidimensional data. The proposed approach addresses the two problems often associated with this task: i) curse of dimensionality ii) cases with small sample sizes. To handle the curse of dimensionality problem, this paper introduces subspace grids and shows how it can be employed for pattern...
Locality sensitive hashing (LSH) has been introduced as an indexing structure for fast large-scale data retrieval. A significant drawback of this technique is that a large number of hash functions require lots of hash computation time. To resolve this issue, the paper presents a new index construction algorithm called boundary-expanding LSH, where the boundary of each bucket is expanded so that each...
Automatic adult video detection is a problem of interest to many organizations around the world. The aim is to restrict the easy access of underage youngsters to such potentially harmful material. Most of the existing techniques are mere extensions of image categorization approaches. In this paper we propose a video genre classification technique tuned specifically for adult content detection by considering...
Multiple linear regression (MLR), the principal components analysis (PCA) and partial least squares (PLS) method are the traditional chemo metric methods in the near infrared spectral analysis. However", "these linear methods could not obtain the very good predicted accuracy. in this paper, the research on application of Fuzzy Pattern Recognition to qualitative analysis of Near infrared...
In this document we present a methodology for movement pattern recognition from arm-forearm myoelectric signals, starting off from the design and implementation of an electromyography (EMG) instrumentation system, considering the Surface EMG for the Non Invasive Assessment of Muscles (SENIAM) rules. Signal processing and characterization techniques were applied using the pass-band Butter worth digital...
Based the analysis of the effect of kernel parameters and penalty parameters on the performance of support vector machine(SVM), the paper has proposed a new method of hydroid simulated annealing technology. The experiment run on the datasets of UCI with the algorithm has shown the result with higher accuracy.
Nowadays, organizations face the problem of keeping their information protected, available and trustworthy. In this context, machine learning techniques have also been extensively applied to this task. Since manual labeling is very expensive, several works attempt to handle intrusion detection with traditional clustering algorithms. In this paper, we introduce a new pattern recognition technique called...
Selective clustering ensemble is usually based on the reference partition to select members of the ensemble. General method of generating reference partition is to use preliminary ensemble results, yet it cannot eliminate the influence of the inferior clustering partitions and the final clustering result is not satisfactory. In order to solve this problem, the paper proposes a new selective clustering...
Automatic classification of modulation type in detected signals is an intermediate step between signal detection and demodulation, and is also an essential task for an intelligent receiver in various civil and military applications. In this paper, a new blind classification method is proposed for additive white Gaussian noise (AWGN) channels with unknown or variable signal to noise ratios. The algorithm...
This paper presents a feature extraction algorithm combining S transform (ST) and two-directional two-dimensional principal component analysis ((2D)2 PCA) for partial discharge (PD) pattern recognition. S transform (ST) is firstly employed to obtain a time-frequency representation of the recorded UHF signals. Then, (2D)2 PCA is applied to compress the ST amplitude(STA) matrices to extract various...
In this paper, we propose a very simple face recognition method. This method first exploits a linear combination of all the training samples to express the test sample. Then it evaluates the capability of each class in expressing the test sample and assigns the test sample to the class that has the strongest capability. Using the expression result, the proposed method can classify the testing sample...
Accuracy assessment is essential after the classification of remote sensed image. For it is expensive for field survey of every sample, how to select an effective sample that is the unbiased estimation of the population which defined as the all the pixels on the classified map is a very important problem. The classification errors are not randomly distributed on the classified map but distributed...
Existing cloud frameworks involve isolating low-level operations within an application for data distribution and partitioning. This limits their applicability for many applications with complex data dependency considerations. This paper aims to explore new methods of partitioning and distributing data in the cloud by fundamentally re-thinking the way in which future data management models will need...
This paper proposes a neural network based framework to classify online Devanagari characters into one of 46 characters in the alphabet set. The uniqueness of this work is three-fold: (1) The feature extraction is just the Discrete Cosine Transform of the temporal sequence of the character points (utilizing the nature of online data input). We show that if used right, a simple feature set yielded...
This paper presents a novel and efficient decision tree construction approach based on C4.5. C4.S constructs decision tree with information gain ratio and deals with missing values or noise. ID3 and its improvement, C4.5, both select one attribute as the splitting criterion each time during constructing decision tree, adopting one step forward. Comparing with one step forward, the proposed algorithm,...
A novel feature extraction method is proposed in this paper. Dislike contour-based or region-based approaches, an object is first converted to a closed curve by extended central projection (ECP). The derived curve not only keeps the affine transform information, but also is very robust to noise. Then whitening transform is performed to the curve such that the affine transformation is simplified to...
This paper aims at presenting a âcomputational costâ optimization method in an Automatic Music Genre Classification system. In such systems, the training and validation database is often enormous. Consequently, a system based on a nearest neighbor classifier suffers from high computational cost during the classification process. In such cases, a training instance clustering (per...
For the diagnosis of liver cancer using a biopsy technique, pathologists¡¦ decisions are mainly based on the spatial and texture information of the biopsy images. However, the diagnostic accuracy strongly depends on the pathologist¡¦s knowledge and experience, that is, such diagnostic results are subjective. Hence, to make an objective and high accuracy diagnosis for the liver cancer in biopsy images,...
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