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Extreme weather recognition using GoogLeNet can achieve excellent performance, which is far superior to the conventional methods. However, the complexity of GoogLeNet is relatively high. Furthermore, for the small scale data, GoogLeNet usually cannot achieve the performance as the large scale data does. In this paper, a novel dual fine-tuning strategy is proposed to train the GoogLeNet model. Firstly,...
Vehicle classification plays an important part in Intelligent Transport System. Recently, deep learning has showed outstanding performance in image classification. However, numerous parameters of the deep network need to be optimized which is time-consuming. PCANet is a light-weight deep learning network that is easy to train. In this paper, a new robust vehicle classification method is proposed,...
Extreme weather always brings potential risk to driving, which leads to people's life and property being put into great dangers. Therefore, the automatic recognition of extreme weather plays an important role in the application of the highway traffic condition warning, automobile auxiliary driving, climate analysis and so on. Generally, multiple sensors are adopted in traditional methods of automatic...
This paper addresses the problem of synthesizing continuous and infinitely varying stream of texture videos by doing operations on finite texture videos. Given an input texture video, such as flame, water, smoke, etc, we can synthesize a longer texture video holding the same texture appearance. Dynamic textures have been modeled as linear dynamic systems (LDS) by unfolding the video frames into column...
In this paper, we focus on developing a novel noise-robust LBP-based texture feature extraction scheme for texture classification. Specifically, two solutions have been proposed to overcome the primary two reasons that cause local binary pattern sensitive to noise. First, a hybrid model is proposed for noise-robust texture description. In this new model, the local primitive micro features are encoded...
This paper uses statistical method to analyzing a budget to managing public financial resources, including revenue change, non tax resources, General Operating Fund Revenues, etc.
The reusing of personal information governed by public sectors becomes an important researching field in the last decade. The existence personal information managing scheme mainly focus on the collection scheme and the storage scheme. However, one other key problem, which is how to distribute the personal information safely, is always ignored. In this paper, a novel chaos-based multi-points secure...
A highly robust chaotic synchronization scheme is proposed in this paper. Different from most synchronization scheme, the two continuous chaotic systems is not driven by each other, but the separated standard digital chaotic systems. Since the digital chaotic systems are not affected by the internal noise and external noise, our synchronization scheme is much more robust than other synchronization...
Chaotic systems have many excellent properties which make them attractive in designing pseudorandom number generator (PRNG). However due to the degeneration phenomenon, the property of chaos-based PRNG with finite precision is poor, e.g. short cycle-length, non-ideal distribution, etc. Therefore, a high efficiency dynamic nonlinear transform arithmetic, which is used to improving the properties of...
Impulsive control of a chaotic system has a great potential for applications in various fields. Therefore, the robustness and stability of impulsive synchronization is very important. In this paper, we introduce a new method for analyzing the robustness and stability of impulsive synchronization with parametric uncertainties and mismatch. By analyzing the oscillation process of the error between two...
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