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Water body extraction from remote sensing image data has been becoming a really hot topic. Recently, researchers put forward numerous methods for water body extraction, while most of them rely on elaborative feature selection and enough number of training samples. Convolution Neural Network (CNN), one of the implementation models of deep learning, has strong capability for two-dimension images’ classification...
Tor is an anonymous communication system that can protect our privacy, but it also provides a haven for criminals to avoid network tracing. Therefore, anonymous traffic analysis and classification is an important part of maintaining network security. Existing Tor traffic classification methods require a large number of labeled data, and the classification accuracy rate is not satisfied for practical...
The recognition and classification of the remote sensing image is a key technology in the application of remote sensing image, which has been one of the research hotspots. Extreme learning machine (EML), is a kind of machine learning method, which has advantages of fast learning speed and good generalization capability, and has been getting more and more attention from the researchers. Based on the...
In this paper, we propose a novel graph kernel specifically to address a challenging problem in the field of cyber-security, namely, malware detection. Previous research has revealed the following: (1) Graph representations of programs are ideally suited for malware detection as they are robust against several attacks, (2) Besides capturing topological neighbourhoods (i.e., structural information)...
In traffic video surveillance system, target-level tracking and feature-level tracking are two important areas for research. Therefore, the combination between them is an interesting question. Mean-shift is a traditional target-level tracking algorithm with no adaptation to vehicle scale and orientation change. In order to solve the problem, algorithm combine SURF (speed-up robust feature) feature...
Along with the inclusion of GPU cores within the same CPU die, the performance of Intel's processor-graphics has been significantly improved over earlier generation of integrated graphics. The need to efficiently harness the computational power of the GPU in the same CPU die is more than ever. This paper presents a highly optimized Haar-based face detector which efficiently exploits both CPU and GPU...
Along with the inclusion of GPU cores within the same CPU die, the performance of Intel's processor-graphics has been significantly improved over earlier generation of integrated graphics. This paper presents a highly optimized SURF cascade based face detector which efficiently exploits both CPU and GPU computing power on the latest Sandy Bridge processor. The SURF cascade classifier procedure is...
In the Brain-computer interface, classification and recognition technology plays an important role, especially the EEG classification and recognition for the movement imagery. In this paper, we use a new type of sensors to collect EEG signals. According to imagine the movement of left or right hand to identify two types of thinking, we proposed a new recognition method based on AR(auto-regressive)...
The performance of a video fingerprinting system, which is usually measured in terms of pairwise independence and robustness, is directly related to the fingerprint that the system uses. This paper has proposed a novel fingerprinting methods base on the gradient orientations of the luminance centroid, which is not only pairwisely independent but also robust against common video processing steps including...
Pulse-Coupled Neural Network (PCNN) is a new kind of network, which is constructed by simulating the activities of the mammal's visual cortex neurons. PCNN is suitable for image processing, including segmentation, image fusion, edge extraction. In this paper, a new method is proposed which is the use of Bidirectional search Pulse-Coupled Neural Network (BPCNN) in the color image segmentation. The...
In the process of iris classification, a new classification distance with adjustable weight which takes advantage of whole phase information to encode is proposed. The method is to use feature extraction function to do the extraction toward all iris image, which could obtain real and imaginary part iris information. Then, tangent function is used to transform extracted real and imaginary part characteristics...
Kaiser function is used to establish clear edge Kaiser filter channel which has selectivity in the frequency and direction with the characteristic of high adaptability and adjustable performance to feature the iris frequency, which is to modify the filter channel edge faintness due to the spectrum leakage when Gabor filter does the data truncation. Then complete classification of the weighted phase...
A pulmonary nodule is relatively round lesion, or area of abnormal tissue located within the lung that can be seen in thoracic CT scans. Because noise and same like disturbance of blood vessels and tracheas, detection of the lung nodule is difficult. A three-dimensional pulmonary nodule detection method for thoracic CT scans is proposed in this paper. First, bounding box method and three-dimensional...
In this article, we present a modified robust image watermarking scheme based on the scale-invariant feature transform (SIFT). The watermark is embedded into some local regions extracted from the original image. During embedding, the initial region is divided into some cirque sub-regions with the same area, and each watermark bit is embedded into one sub-region. Besides, it is embedded in the non-subsampled...
To realize the information integration of CAD/CAPP/CAM, itpsilas important to apply the feature recognition method to the transfer and share of part information, but itpsilas still very difficult to apply the feature recognition method to handle the complicated box part. This paper presents a new method to extract the box part information, called as ldquofeature naming methodrdquo, this method can...
The idea of representing images using a bag of visual words is currently popular in object category recognition. Since this representation is typically constructed using unsupervised clustering, the resulting visual words may not capture the desired information. Recent work has explored the construction of discriminative visual codebooks that explicitly consider object category information. However,...
A novel multifocus image fusion algorithm based on contourlet transform and region statistics was proposed. For good properties of multiscale, localization, directionality and anisotropy, the multifocus source images are first decomposed using contourlet transform. Fusion operations based on region statistics are implemented for all subbands in each scale and direction. Regional variance and local...
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