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Visual object tracking is an important problem in computer vision and has many applications including traffic monitoring, augmented reality and human computer interface. Although it has been investigated in the past decades, designing a robust tracker to cope with different objects under various situations is still a great challenging task. Focusing on the single-target tracking problem, this paper...
Musical instruments are consist of wide variety of domain so manual classification of these instruments is difficult and challenging task. To make the process of classifying musical instrument easy and less dependent on human supervision given system is designed. There are some algorithm are available for classification tsk from which we uses SVM, MLP and AdaBoost for better result. This system mainly...
AdaBoost is a classic ensemble learning algorithm with good classifier performance. In the past, it mainly used weak classifier as base classifier, such as KNN. They are simple and easy to train, but the essence of the weak classifier, it is impossible to get very high classification accuracy. In order to improve the correct rate, this paper introduces the AdaBoost ensemble classifier based on convolutional...
Sentiment mining from sources like Twitter which contain informal texts is needed as there is prominent information and vast amount of data to be analyzed, understood and experimented. There has been a lot of research in this area to get the semantic information from this domain and to create better prediction in terms of Sentiment classification. We present a novel approach which provides an ensemble...
This paper gives the hardware implementation of face detection on FPGA using Haar features. The design consisting of integral image generation which is used to compute the Haar features at a faster rate, has been illustrated. The classifiers are built using the AdaBoost algorithm which selects a minimum number of critical Haar features from a very large set. Also, parallel processing classifiers increase...
Diabetic Retinopathy is human eye disease which causes damage to retina of eye and it may eventually lead to complete blindness. Detection of diabetic retinopathy in early stage is essential to avoid complete blindness. Many physical tests like visual acuity test, pupil dilation, optical coherence tomography can be used to detect diabetic retinopathy but are time consuming and affects patients as...
The CS framework is useful for a much wide rangeof pattern recognition tasks such as visual object classification. It is possible to directly extract features from a small numberof random projections without ever reconstructing the signal, which results in compressed learning. As for compressedlearning, it is to learn with randomly projected data, compressed data, instead of original data. Learning...
Lung cancer is one of the primary causes of cancer-related death worldwide. A computer-aided detection (CAD) can help radiologists by offering a second opinion and making the whole process faster at an early level. In this study, we propose a new classification approach for pulmonary nodule detection from CT imagery by using morphological features of nodule patterns. Ensemble learning approaches are...
Goal: The purpose of this study is to evaluate the usefulness of the boosting algorithm AdaBoost (AB) in the context of the sleep apnea-hypopnea syndrome (SAHS) diagnosis. Methods: We characterize SAHS in single-channel airflow (AF) signals from 317 subjects by the extraction of spectral and nonlinear features. Relevancy and redundancy analyses are conducted through the fast correlation-based filter...
In this paper, the shape features of different material of flame and interference image in video fire detection were analyzed and compared. The area, perimeter, rotundity, solidity, extent, sharp corners, similarity and centroid displacement are selected as the candidate features. After analyzing and excluding area and perimeter as these candidate features, weak classifiers of six other shape features...
This paper proposes an occluded face detection technology based on the Adaboost algorithm. In this paper, we select moving regions for detection using a background subtraction method. The upper half and lower half parts of human face are detected respectively in moving regions by facial detector which was trained based on Adaboost algorithm and Haar features. Our experimental results indicate the...
The detection of faces in an image is a subject often studied in computer vision literature. The algorithm which allowed face detection, imposing new standards in this area, was the Viola - Jones algorithm. In this paper, a practical implementation of a face detector based on Viola-Jones algorithm using Matlab cascade object detector is presented. Employing the system type object vision.CascadeObjectDetector,...
Intrusion Detection System (IDS) is a tool for anomaly detection in network that can help to protect network security. At present, intrusion detection systems have been developed to prevent attacks with accuracy. In this paper, we concentrate on ensemble learning for detecting network intrusion data, which are difficult to detect. In addition, correlation-based algorithm is used for reducing some...
An approach for keyframe extraction using AdaBoost is proposed which is based on foreground detection. The aim of this approach is to extract keyframes from sequences of specific vehicle images of lane vehicle surveillance video. This method utilizes integral channel features and the area feature as the image feature descriptor, combined with training an AdaBoost classifier. The experimental results...
Adaptive boosting (AdaBoost) can boost a weak learning algorithm with an accuracy slightly better than random guessing into an arbitrarily accurate strong learning algorithm. It has been applied to target recognition with single feature classifier. However, the poor discriminative power of extremely weak single feature classifier limits its application. In this paper, we present a novel comprehensive...
Alternative splicing (AS) is a mechanism for generating different gene transcripts (called isoforms) from the same genomic sequence. Accurate classification of alternative splicing is important for understanding the mechanism of gene regulation. Although the different algorithms are applied to classify AS, the accuracy of these algorithms are still unsatisfactory. In this paper, we propose a new classification...
This paper describes the technique for real time human face detection and tracking using a modified version of the algorithm suggested by Paul viola and Michael Jones. The paper starts with the introduction to human face detection and tracking, followed by apprehension of the Vila Jones algorithm and then discussing about the implementation in real video applications. Viola jones algorithm was based...
Microscopic examination of a properly prepared blood smear is valuable in complete blood count (CBC) and differential blood count (DBC). A hematopathologist may spend enormous time manually inspecting the good working area (GWA) of the blood smear under a light microscope system to perform CBC or DBC. In this paper we focus on automatic localization of the GWA by classifying microscopic images of...
This paper focuses on improving the performance of Adaboost (Adaptive Boosting) by using weak classifiers that make classification with a confidence score. Single thresholds and nearest neighbor classifiers are used as base classifiers. The proposed method is applied to the problem of pedestrian detection in still images. Haar-like basic features are used to construct weak classifiers.
In this paper, a new method to manage graduation photography is introduced. First, AdaBoost algorithm, which can achieve high detection accuracy, is adopted to detect faces in the graduation photography. After adjusting the position and adding the missed faces, the personal information of each photography is added into database. To get the current status of graduates, one can send emails to the member...
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