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In this letter, an attitude estimation method is presented for space targets by using an inverse synthetic aperture radar (ISAR) image sequence. The line structures, like the boundaries of planar payloads, are extracted from the ISAR image sequence and associated from frame to frame. With the accommodation of the radar looking angle information from the trajectory, the threedimensional attitude of...
This paper proposes a regrouping particle swarm optimization-based neural network (RegPSONN) for rolling bearing fault diagnosis. The proposed method applied neural network for rolling bearing conditions classification, and regrouping particle swarm optimization (RegPSO) is utilized for network training, and ten time-domain feature parameters are selected to establish the input vector. To evaluate...
Attention based recurrent neural networks have achieved great success in answer selection, which is an important subtask of question answering (QA). However, previous work used fixed representation of question to compute the attention information for answers, which fails to extract the influence that answers make on question. In our work, we propose a coattention based bidirectional LSTM for answer...
This paper presents a model-based Field Programmable Gates Array (FPGA) design for real-time feature extraction of Electroencephalogram (EEG) signals, which can be used for brainwaves bands classification to track and detect mental status in Brain Computer Interface (BCI) applications and consciousness studies. An model-based design approach is used to implement Short-time Fourier Transform (STFT)...
In this paper, we proposed new framework for human action representation, which leverages the strengths of convolutional neural networks (CNNs) and the linear dynamical system (LDS) to represent both spatial and temporal structures of actions in videos. We make two principal contributions: first, we incorporate image-trained CNNs to detect action clip concepts, which takes advantage of different levels...
This paper proposes a lightweight deep model to recognize age and gender from a face image. Though simple, our network architecture is able to complete the two tasks effectively and efficiently. Moreover, different from existing methods, we simultaneously perform the age and gender recognition tasks via a joint regression model. Specifically, our model employs a multi-task learning scheme to learn...
Previous research on sentiment classification by machine learning algorithms has shown that they usually work well with large-scale dataset. However, most open datasets for Chinese sentiment classification are quite small. In this paper we build a large-scale annotated Chinese sentiment dataset by filtering a vast amount of human-computer conversations. We conduct thorough experiments by using Convolutional...
Automatic detection of pavement cracks is an important task in transportation maintenance for driving safety assurance. However, it remains a challenging task due to the intensity inhomogeneity of cracks and complexity of the background, e.g., the low contrast with surrounding pavement and possible shadows with similar intensity. Inspired by recent success on applying deep learning to computer vision...
The common spatial pattern (CSP) is extensively used to extract discriminative feature from raw Electroencephalography (EEG) signals for motor imagery classification. The CSP is a statistical signal processing technique, which relies on sample based covariance matrix estimation to give discriminative information from raw EEG signals. The sample based estimation of covariance matrix becomes a problem...
Android has become the most popular mobile platform due to its openness and flexibility. Meanwhile, it has also become the main target of massive mobile malware. This phenomenon drives a pressing need for malware detection. In this paper, we propose TrafficAV, which is an effective and explainable detection of mobile malware behavior using network traffic. Network traffic generated by mobile app is...
A 3D motion detection method based on RGB-D data and scene flow clustering is proposed in this paper. The 3D extension of the optical flow called scene flow which describes the 3D motion of every point in a scene between two consecutive frames. Firstly, we estimate the scene flow using color maps and the aligned depth maps in two consecutive frames, then extract the feature vector of each point from...
Malware data are typically depicted with extremely high-dimensional features, which lays an excessive computational burden on detection methods. For the sake of effectiveness and efficiency, feature selection is an indispensable part for malware detection. In this paper, we propose an ensemble feature selection method with integration of discriminative and representative properties for malware detection...
We propose a method for extraction of equivalent circuit model for on-chip spiral inductor. The method is based on optimization of circuit elements based on feature points extracted from frequency dependent response. The accuracy of the method is validated by extracting a set of models from electromagnetic simulations of on-chip rectangular spiral inductors. An excellent agreement is achieved between...
Strokes of Chinese characters are extracted from a picture of calligraphy work by image processing methods. By analyzing the stroke's centerline location, width, constriction velocity and curvature, a feature matrix is constructed. By editing the feature matrix, we synthesize images of Chinese calligraphy in new styles.
More and more advanced persistent threat attacks has happened since 2009. This kind of attacks usually use more than one zero-day exploit to achieve its goal. Most of the times, the target computer will execute malicious program after the user open an infected compound document. The original detection method becomes inefficient as the attackers using a zero-day exploit to structure these compound...
An object recognition method based on Gabor wavelet and SVM is proposed in this paper. First features of the object are extracted by using Gabor wavelet, and then the dimensions of the Gabor features are reduced with Principal Component Analysis, and finally classification is performed with Support Vector Machine. And this method is applied to the Columbia image library COIL-20 for experiments. Compared...
Feature and metric researchings are two vital aspects in person re-identification. Metric learning seems to have gained extra advantage over feature in recent evaluations. In this paper, we explore the neglected potential of feature designing for re-identification. We propose a novel and efficient person descriptor, which is motivated by traditional spatiogram and covariance descriptors. The spatiogram...
Various binary features have been recently proposed in literature, aiming at improving the computational efficiency and storage efficiency of image retrieval applications. However, the most common way of using binary features is voting strategy based on brute-force matching, since binary features are discrete data points distributed in Hamming space, so that models based on clustering such as BoW...
Bridge plays an important role in people's life. The automatic bridge detection has great value especially in disaster situation. In this paper, we propose an automatic bridge detection method in multispectral image to detect bridges over water. First, we extract the water region using NDWI index method by taking the advantage of the spectrum properties of water. Second, the water region is extended...
This paper proposes an Android malware detection approach based on attack tree. Attack tree model is extended to provide a novel way to organize and exploit behavior rules. Connections between attack goals and application capability are represented by an attack tree structure and behavior rules are assigned to every attack path in the attack tree. In this way, fine-grained and comprehensive static...
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