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Recognizing Biomedical Named Entities (BioNEs) such as genes, proteins, cells, drugs, diseases, etc. play a vital role in many Biomedical Text Mining applications. BioNER fall into five approaches: Dictionary-Based, Rule-Based, Machine-Learning-Based, Statistical-Based, and Hybrid-Based. Methods Based Machine Learning approach, are more effective than those of other approaches, and therefore have...
A new method of tool wear intelligence measure based on Support Vector Machine(SVM) and Hidden Markov Models (HMM) is proposed to monitor tool wear and to predict tool failure. At first, FFT features are extracted from the model signal of the tool in cutting process, then FFT vectors are introduced to SVM-HMM for machine learning and classification. The signal of Tool wear in cutting process is introduced...
In order to solve the problems of current machine learning in fault diagnosing system of the chemical plants, a better and effective multilayer architecture model is used in this paper. Hidden Markov model (HMM) is good at dealing with dynamic continuous data and support vector machine (SVM) shows superior performance for classification, especially for limited samples. Combining their respective virtues,...
This paper presents a new approach for event detection from video surveillance data based on optical fow histogram with no prior knowledge of the motion nature. First,we start by estimating the motion from images sequence using optical flow technique. Second, we perform a classification using the histogram of the optical flow vectors and we use a chain coding algorithm that we applied to each class...
In this paper, we present a novel approach for incorporating structural information into the hidden Markov modeling (HMM) framework for offline handwriting recognition. Traditionally, structural features have been used in recognition approaches that rely on accurate segmentation of words into smaller units (sub-words or characters). However, such segmentation based approaches do not perform well on...
This paper presents a novel approach to recognize similar handwritten numerals based on empirical mode decomposition (EMD). We firstly use the local maximum modulus of wavelet transform (MMWT) to get the width-invariant and grey-level invariant characterization of contours in an image. Then we apply EMD analysis to decompose the synthetic shift normalization of curvature into their components, which...
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