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This paper aims to develop an effective flower classification approach using the technology of feature extraction. With this regard, a fused descriptor based on Pyramid Histogram of Visual Words (PHOW) is used to extract the color, texture and contour information of flower image. Secondly, Dictionary Learning and Locality-constrained Linear Coding (LLC) are operated on PHOW feature and then images...
Band selection is a very important hyperspectral image preprocessing before using data. A novel bands selection method for hyperspectral data based on convolutional neural network (CNN) is proposed in this paper. In this way, we use a custom one-dimensional CNN to train the hyperspectral data to obtain a well-trained model. After testing band combinations, we use the model to obtain the test precision...
This paper presents a probabilistic kernel learning based Gaussian mixture distributions in medical images registration. Gaussian distributions lie on Riemannian manifold, where high dimensional data possesses rich geometry structures. However, nonlinear geometry of Riemannian manifold in linear space gives rise to inferior registration results. Accordingly, kernel method is used to embed a given...
In recent years, the rapid development of virtualization and container technology brings unprecedented impact on traditional IT architecture. Trusted Computing devotes to provide a solution to protect the integrity of the target platform and introduces a virtual TPM to adapt to the challenges that virtualization brings. However, the traditional integrity measurement solution and remote attestation...
In this paper, a novel kernel low rank representation (KLRR) method for hyperspectral image classification is proposed. Firstly, we extract the global structure characteristics information of the hyperspectral image based on low rank representation (LRR), then use it as a prior to constrain the recovery coefficient matrix. In order to further improve the classification efficiency and deal with the...
To build an experimental platform for wireless sensor networks based on 802.11 high rate data transmission protocol, AODV-UU and DSR-UU high rate routing protocols are implemented on the Smart210 development board with embedded Linux operating systems in this paper. In a real static environment, the average end to end delay, packet loss rate and throughput of the network system are tested and compared...
Software defined radio (SDR) plays an important role in military and commerce because of its inherent flexibility. It also has great potential in home use, and it can be controlled by software installed on a personal computer or embedded system to achieve different purposes. In this paper, a novel method of dynamic gesture recognition based on support vector machine (SVM) and SDR is proposed. It is...
Pedestrian detection exhibits important application value in driver assistance systems, The detection performance often suffers from the various appearances of pedestrians, the illumination changes and complex background. Aiming at solving these challenges, in this paper, first, a new color moments feature is presented to describe the local similarity structure of pedestrians, which reduces the influence...
Automatic analysis of histopathological images has been widely investigated using computational image processing and machine learning techniques. Computer-aided diagnosis (CAD) systems and content-based image retrieval (CBIR) systems have been successfully developed for diagnosis, disease detection, and decision support in this area. In this paper, we focus on a scalable image retrieval method with...
Recent years have witnessed the growing popularity of hashing in large-scale vision problems. It has been shown that the hashing quality could be boosted by leveraging supervised information into hash function learning. However, the existing supervised methods either lack adequate performance or often incur cumbersome model training. In this paper, we propose a novel kernel-based supervised hashing...
Underwater acoustic communication systems need Doppler compensation for the server Doppler effects. OFDM (Orthogonal Frequency Division Multiplexing) is widely applied in the underwater acoustic communication systems. FFT is the most computational kernels in the OFDM systems. By exploring the two typical digital signal processing kernels and other basic kernels, an ASIP (Application Specific Instruction...
Kernel-level attacks can compromise the security of an operating system by tampering with key data and control flow in the kernel. Current approaches defend against these attacks by applying data integrity or control flow integrity control methods. However, they focus on only a certain aspect and cannot give a complete integrity monitoring solution. This paper tries our best to find out all resorts...
Image registration is an indispensable process in the detection of brain structural and anatomical abnormities. Inverse-consistency, topology preserving and real time application are essential to provide accurate deformation fields for statistical analysis of brain variability. Unfortunately, the previous algorithms lacked of these features. We present a registration method by adapting the optimization...
Accurate grid resources prediction is crucial for a grid scheduler. In this study, support vector regression (SVR), which is an effective regression algorithm, is applied to grid resource prediction. In order to obtain better prediction performance, SVR's parameters must be selected carefully. Therefore, a particle swarm optimization-based SVR (PSO-SVR) model, in which PSO is used to determine free...
Facial expression extraction is the essential step of facial expression recognition. The paper presents a system that uses 28 facial feature key-points in images detection and Gabor wavelet filter provided with 5 frequencies, 8 orientations. In according to actual demand, It can extract the feature of low quality facial expression image target, and have good robust for automatic facial expression...
Service-oriented computing (SOC) is a kind of computing paradigm that utilizes services as fundamental elements for developing applications. In study domain of SOC, modeling and analysis of services-oriented software requirements is an important research direction. Because of frequent changes of individual or collective requirements and continuous evolution of system function & structure, the...
In this paper, a novel learning method based on kernelized fuzzy clustering and least squares support vector machines (LSSVM) is presented to improve the generalization ability of a Takagi-Sugeno-Kang (TSK) fuzzy modeling. Firstly, the fuzzy partition of the product space of input and output is obtained by kernelized fuzzy clustering. Then, a computationally efficient numerical method is proposed...
Object detection is an important function for intelligent multimedia processing, but its computational complexity prevented its pervasive uses in consumer electronics. Cost-effective & energy-efficient computations are now available with various innovative multicore architectures proposed for embedded systems. However, extensive software optimizations are needed to unravel the inherent parallelisms...
In order to overcome the dimension problem of the traditional fuzzy clustering, we use kernel-based fuzzy c-means clustering (KFCM) to construct first-order TSK fuzzy models. The proposed algorithm is composed of two phases. In the first phase, the antecedent fuzzy sets are obtained by KFCM. We present the expression of the cluster prototypes of KFCM with different kernel functions in original input...
Clustered microcalcification is an important signal for breast cancer in the early stages. In this paper, we propose a multiple kernel SVM with group features (GF-SVM) to tackle problems associated with heterogeneous features of clustered microcalcification and normal breast tissues in suspicious regions. Specifically, different types of features such as being gradient, geometric and textural are...
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