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This paper proposes a method for rapid and continuous monitoring of slope deformation by using terrestrial optical photogrammetry. This slope monitoring method is non-contact and has a high speed to calculate the position and displacement of slope points, which can be applied to the continuous observation and disaster warning of the problem area of the slope. The theory of this method is to obtain...
In classification, a large number of features often make it difficult to select appropriate classification features. In such situations, feature selection or dimensionality reduction methods play an important role in classification. ReliefF algorithm is one of the most successful filtering feature selection methods. In this paper, some shortcomings of the ReliefF algorithm are improved, on the problem...
Many recent applications require text segmentation for born-digital compound images. To this end, we propose a coarse-to-fine framework for segmenting texts of arbitrary scales and orientations in born-digital compound images. In the coarse stage, the local image activity measure is designed based upon the variation distribution of characters, to highlight the difference between textual and pictorial...
Over-complete ICA problem are always met in engineering applications. That is to say, the number of unknown sources is more than the number of observed signals. At this time basic ICA model is not suitable. This text utilizes the component of priori knowledge as additional input signal (addition virtual channel), to increase the number of the input signals. And it can solve the engineering application...
Independent component analysis of a single measured mixing signal, that is single channel Independent component analysis (SCICA), has been widely used in feature extraction of a signal. In this paper we provide a example of using single channel ICA for extracting the feature of a abnormal running condition of a turbine from measured vibration signals, in order to show the effect of SCICA. The bearing...
Illumination variation is one of the most difficult problems for face recognition. In this paper, we represent a new ordinal feature based method for face recognition under varying illumination. We employ 2-D wavelet transform to compress face images and extract ordinal features from them. Here, the ordinal feature is extracted more easily than before and competent for face recognition, which is invariant...
Local ridge regression classifier (LRR) is an effective local face recognition method. It suppresses the influence of local changes by setting a voting RR classifier for each image region, thus has partial robustness to local changes caused by lighting, occlusions and poses. LRR uses the concatenated vector of a sub-image as its input feature, such a feature is still not sufficient to represent an...
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