With the development of economy, steel has been widely used by human beings in various fields of social life, for example, military products, vehicles, aerospace, high-rise buildings and daily necessities. Therefore, ...
详细信息
In this paper, a novel approach for image visual saliency detection is proposed from both the salient object (foreground) and the background perspective. To better highlight the salient object, we start from what is a...
详细信息
Protein subcellular localization prediction is im- portant for studying the function of proteins. Recently, as significant progress has been witnessed in the field of mi- croscopic imaging, automatically determining t...
详细信息
Protein subcellular localization prediction is im- portant for studying the function of proteins. Recently, as significant progress has been witnessed in the field of mi- croscopic imaging, automatically determining the subcellular localization of proteins from bio-images is becoming a new research hotspot. One of the central themes in this field is to determine what features are suitable for describing the pro- tein images. Existing feature extraction methods are usually hand-crafted designed, by which only one layer of features will be extracted, which may not be sufficient to represent the complex protein images. To this end, we propose a deep model based descriptor （DMD） to extract the high-level fea- tures from protein images. Specifically, in order to make the extracted features more generic, we firstly trained a convolu- tion neural network （i.e., AlexNe0 by using a natural image set with millions of labels, and then used the partial parame- ter transfer strategy to fine-tnne the parameters from natural images to protein images. After that, we applied the Lasso model to select the most distinguishing features from the last fully connected layer of the CNN （Convolution Neural Net- work）, and used these selected features for final classifica- tions. Experimental results on a protein image dataset vali- date the efficacy of our method.
In this paper, we propose a scatter-glare correction method based on thickness estimation and digital filtration. The method is an improvement of the scatter-glare correction method proposed by Ersahin, et al. The met...
详细信息
In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these i...
详细信息
In conventional image matching methods, the image matching process is mostly based on image statistic information. One aspect neglected by all these methods is that there is much fuzzy information contained in these images. A new fuzzy matching algorithm based on fuzzy similarity for navigation is presented in this paper. Because the fuzzy theory is of the ability of making good description of the fuzzy information contained in images, the image matching method based on fuzzy similarity would look forward to producing good performance results. Experimental results using matching algorithm based on fuzzy information also demonstrate its reliability and practicability.
A simple method is proposed to estimate the DOA using acoustic vector sensor in the presence of nonuniform noise. Algorithms mentioned in earlier works are shown to be susceptible to choice of weighted parameter. The ...
详细信息
With the unprecedented growing of city economy and the crying need for public transportation, the ease of traffic related problems such as traffic jams has been a hard nut to crack everywhere. In this paper, a new met...
详细信息
Based on the analysis of the groove images in gas metal arc welding with small slope angle, a new algorithm of the groove edge location is presented. The groove edge was effectively detected by combining Roberts Detec...
详细信息
Based on the analysis of the groove images in gas metal arc welding with small slope angle, a new algorithm of the groove edge location is presented. The groove edge was effectively detected by combining Roberts Detector with the general non linear gradient operator. In addition, using Norton Quadratic Polynomial Interpolation, the edge location precision reached sub pixel level. The experimental results show that the edge detection system works well under the condition of short transfer arc welding.
In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can pr...
详细信息
In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can provide good discriminative representations of both target and background. We accomplish this by exploiting the recovery ability of low-rank matrices. That is if we assume that the data from the same class are linearly correlated, then the corresponding basis vectors learned from the training set of each class shall render the dictionary to become approximately low-rank. The proposed dictionary learning technique incorporates a reconstruction error that improves the reliability of classification. Also, a multiconstraint objective function is designed to enable active learning of a discriminative and robust dictionary. Further, an optimal solution is obtained by iteratively computing the dictionary, coefficients, and by simultaneously learning the classifier parameters. Finally, a simple yet effective likelihood function is implemented to estimate the optimal state of the target during tracking. Moreover, to make the dictionary adaptive to the variations of the target and background during tracking, an online update criterion is employed while learning the new dictionary. Experimental results on a publicly available benchmark dataset have demonstrated that the proposed tracking algorithm performs better than other state-of-the-art trackers.
Vehicle detection is one of the key technologies in Intelligent Transportation System (ITS), and it i an important stage of vehicle tracking in visual surveillance. Due to the clutter of traffic scenes, the captured v...
详细信息
暂无评论