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For remote sensing image understanding, target detection is one of the most important tasks. In this paper, we propose one object detection method based on region proposal detection via active contour model and detection based on one-class classification method. The large scale remote sensing image is split into several connected components. And then, the proposed algorithm detects the object from...
Manual wafer-level die inking is a common procedure for excluding die locations that are likely to be defective. Although this is a more cost-effective process, as compared to the expensive burn-in tests, it remains a labor-intensive step during IC testing. For each manufactured wafer, test engineers have to visually inspect every failure map in order to identify any regions where additional die need...
In this paper, we try to recognize negative emotions (sadness and disgust) of human affecting driving by using physiological signals that are commonly used to deal with human emotions. To do this, emotional stimuli are used to induce sadness and disgust, and emotion recognition is performed based on the feature vector extracted from the physiological signals collected on the induced emotion by a stimulus...
In this paper we shall present recent results of two applications for monitoring using acoustical signal classification. The first case study is the problem of context awareness based on acoustic analysis for a service robot. Then we discussed the acoustic classification for wildlife intruder detection. Previous results are briefly recalled and new experimental results are also provided.
The classification and identification of the bird species from the visual image is complex compared by using audio song. The knowledge of the features species type is very important as to ensure it is classified to the correct species. Color-based feature extraction is one of the procedure in extracting the color properties from the bird which to represent the species of the bird. However, it is a...
The interoperability testing of CTCS-3 Level Train Control System guarantees the safe operation of train running on different lines. It makes great sense to achieve automatic analysis of interoperability testing results, which could improve the efficiency and accuracy of testing. In this paper, a research was conducted on automatic analysis of testing results for on-board equipment of train control...
Every organism emits energy around it which comprises UV-radiation, EM-radiation, infrared and thermal radiation. This energy around human body represents health condition of the subject under study. These energy fields are called as aura of the body under consideration. Several types of equipments are there to capture such energy. Kirlian camera captures the distribution of energy radiation around...
Coreference resolution plays a significant role in natural language processing systems. It is the method of figuring out all the noun phrases that refer back to the identical real world entity. Several researches have been done in noun phrase coreference resolution by using certain machine learning techniques. Our paper proposes a machine learning approach using support vector machines (SVM) towards...
Identity recognition encounters with several problems especially in feature extraction and pattern classification. Electrocardiogram (ECG) is a quasi-periodic signal which has highly discriminative characteristics in a population for subject recognition. The personal identity verification in a random population using kernel-based binary and one-class Support Vector Machines (SVMs) has been considered...
In this paper, we use machine learning for profiling authors of online textual media. We are interested in determining the gender and age of an author. We use two different approaches, one where the features are learned from raw data and one where features are manually extracted.We are interested in understanding how well author profiling works in the wild and therefore we have tested our models on...
Goal: the objective of this study was to develop a method to identify respiratory phases (i.e., inhale or exhale) of seismocardiogram (SCG) cycles. An SCG signal is obtained by placing an accelerometer on the sternum to capture cardiac vibrations. Methods: SCGs from 19 healthy subjects were collected, preprocessed, segmented, and labeled. To extract the most important features, each SCG cycle was...
This research proposes a reliable machine learning based computational solution for human detection. The proposed model is specifically applicable for illumination-variant natural scenes in big data video frames. In order to solve the illumination variation problem, a new feature set is formed by extracting features using histogram of gradients (HoG) and linear phase quantization (LPQ) techniques,...
This paper describes a preliminary investigation of Voice Pathology Detection using Deep Neural Networks (DNN). We used voice recordings of sustained vowel /a/ produced at normal pitch from German corpus Saarbruecken Voice Database (SVD). This corpus contains voice recordings and electroglottograph signals of more than 2 000 speakers. The idea behind this experiment is the use of convolutional layers...
To study the characteristics and performance of the deep learning in intelligent intrusion detection, two hybrid algorithms, which combine restricted Boltzmann machine (RBM) with support vector machine (SVM) and deep belief network (DBN) respectively, are used to analyze the accuracy, false positive rate, false negative rate and testing time with the data set used for The Third International Knowledge...
The aim of this paper is to classify the object in hyper spectral images which are high dimensional images and consists of many data channels. Another aim is to use machine learning classification algorithm like support vector machine (SVM) which is good for high dimensional data case. SVM provides a good accuracy of classification. A statistical model is developed to learn and classify hyper spectral...
Human gesture recognition is a rather new field and many challenges, sign language recognition is a concrete example of gesture recognition. In this paper, we study the feasibility and effectiveness of vector machine learning methods, namely Support Vector Machine (SVM), Simplification of Support Vector Machine (SimpSVM) and Relevance Vector Machine (RVM) to the sign language recognition problem....
Texture classification is a problem that has variousapplications such as remote sensing and forest speciesrecogni- tion. Solutions tend to be custom fit to the datasetused but fails to generalize. The Convolutional NeuralNetwork (CNN) in combination with Support Vector Machine(SVM) form a robust selection between powerful invariantfeature extractor and accurate classifier. The fusion ofexperts provides...
Online shopping is one of the most comfortable ways to shop in this new era of technology. People buy online products frequently and post their reviews about the products they have used. The viewpoint of the user will be in the form of tweets or product reviews which they post in an e-commerce site. These reviews will have significant role in deciding how far the products have been placed in peoples...
In this paper, a blind bandwidth extension algorithm for music signals has been proposed. This method applies the K-means algorithm to firstly cluster audio data in the feature space, and constructs multiple envelope predictors for each cluster accordingly using Support Vector Regression (SVR). A set of well-established audio features for Music Information Retrieval (MIR) has been used to characterize...
Predicting a person's gender based on the iris texture has been explored by several researchers. This paper considers several dimensions of experimental work on this problem, including person-disjoint train and test, and the effect of cosmetics on eyelash occlusion and imperfect segmentation. We also consider the use of multi-layer perceptron and convolutional neural networks as classifiers, comparing...
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