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For low density crowd, the statistical information of pixels and feature points can reflect the change of crowd density. Therefore, pixels and corners are fused in this paper, then, SVR is used to learn the corresponding relationship between feature and the number of people. While PSO is used to optimize the choice of parameters C and gamma in SVR. The experimental results show that the SVR optimized...
In this paper, we present an improved motion estimation method by adding extra information for binocular visual odometry (VO) which is especially suited for improving high-speed pose change estimation. The extra information is obtained by structured object detecting, taking lane line detection as an example. We can get an accurate position information by calculating the interval of each dotted lane...
The dispatching of labor and distribution of tasks among workers are important aspects of corporate operations. Labor dispatch refers to the dispatching of employees to meet with clients; however, dispatches commonly vary with time. This means that any analysis pertaining to labor dispatch and work distribution should also vary with time. In this study, MATLAB was used to analyze data from anonymous...
In this work, we introduce a Deep Neural Network model for automated software categorization. The model is ableto form high-level concepts from low-level code tokens andto distinguish important features such as API calls and identifiersin order to support software categorization. Our empirical evaluationshows that DNN outperformed other machine learning approacheswith 15.9–36.4% higher accuracy in...
Objective For low-voltage current transformer surface crack detection, traditional methods can not effectively distinguish cracks and scratches problem, crack detection method is proposed based on geometrical features and Moment Invariant. Method Extraction algorithm by osmosis from the gray image of the target area, according to the crack and scratches different texture features, the use of geometric...
Image stitching technique is to integrate multiple images with overlapping regions into a complete image with a wide viewing angle, less distortion, and no obvious suture. Image stitching could be used for global positioning and robot autonomous navigation without changing the hardware. SIFT feature and SURF feature are the classical algorithm in the image stitching. But they have the long time-consuming...
It is attractive to extract and determine the key features of traffic patterns for mitigating road congestion and predicting travel time of vehicles in traffic analysis. Based on previous works that is a scalable approach via Hadoop MapReduce programming model, and can extract maximal repeats from a huge amount of tagged sequences, this paper adapts that approach to extract significant patterns of...
App repackaging is a common threat in the Android ecosystem. To face this threat, the literature now includes a large body of work proposing approaches for identifying repackaged apps. Unfortunately, although most research involves pairwise similarity comparison to distinguish repackaged apps from their "original" counterparts, no work has considered the threat to validity of not being able...
In this work, an image processing based lane-detection approach is proposed. In the proposed approach, candidate pixels that can be used for lane markings are detected by making use of 1-bit transform as a pre-processing step. Next, feature points are extracted via Sobel filter and candidate lane markings are decided employing a correlation and Hough transform based approach. Finally, Kalman filter...
In recent years, fast development of video editing software has made video forgery applicable. One of the most frequently encountered forgery types in video forensics is the frame duplication forgery. Researches have proposed methods to deal with this type of forgery. The two main drawbacks of this methods reported in the literature are execution time and low detection accuracy. In this work a new...
Rice Planthopper (RPH) infestation in paddy field is a serious disaster in Asia every year. Finding RPHs based on image processing is an important thing before RPHs growth. We propose a region of interest (ROI) method to detect RPHs clearly. First, get rectangle ROI in HSV space and do color analysis. By using decision tree algorithm, classify analytic data to get binary image of RPHs. The results...
This paper presents a novel unsupervised image classification method for polarimetric synthetic aperture radar (PolSAR) data. The proposed method is based on a discriminative clustering framework that explicitly relies on a discriminative supervised classification technique to perform unsupervised clustering. To implement this idea, we design an energy function for unsupervised PolSAR image classification...
Brain computer interface applications have big importance in becoming a bridge between the human brain and devices. The studies in this area increase every day with the use of different feature extractions and classification methods In this study, classification is done by Random Forest method using Data Set III presented in BCI Competiton 2003, and it has been shown that combining the Fast Walsh...
Feature-oriented software development (FOSD) has recently emerged as a promising approach for developing a collection of similar software products from a shared set of software assets. A well-recognized issue in FOSD is the analysis of feature interactions: cases where the integration of multiple features would alter the behavior of one or several of them. Existing approaches to detecting feature...
In iMs paper, a novel method for extracting radar fingerprint using the unintentional modulation on radar signals is proposed. Proposed technique decomposes the unintentional modulations into its components using Variational Mode Decomposition (VMD) technique. Then, features that characterize each component are calculated. Simulations using real radar data show that proposed technique can classify...
In today's technology, the data collection processes have to deal with simultaneous data sources. In order, for the data to be examined or used by artificial learning methods, the data incoming from different sources must be aligned with each other. In this research, participants have worn eye tracker devices and all watched segments in the prepared experimental environment have been recorded as a...
With the increased use of smart devices, digital cameras and abundance of memory in the devices, the pictures of the same scenes have been taken several times, resulting in a number of images consisting of the same or very similar content in memory. Manually selecting the good ones is time-consuming as well as error prone. In this paper, the features of the images in the data sets were extracted and...
The use of depth sensors in activity recognition is a technology that emerges in human computer interaction and motion recognition. In this study, an approach to identify single-person activities using deep learning on depth image sequences is presented. First, a 3D volumetric template is generated using skeletal information obtained from a depth video. The generated 3D volume is used for extracting...
A novel extension to Hızlı B-ESA object detection algorithm is proposed in order to learn convolutional context features for determining boundaries of objects better. For input images, the hypothesis windows and their context around those windows are learned through convolutional layers as two parallel networks. The resulting object and context feature maps are combined in such a way that they preserve...
Deep learning is a form of hierarchical learning, it consists of multiple layers of representations that gradually transform data into high level concepts. Deep learning has been providing the state of the art results for various computer vision problems. However, a typical deep leaning algorithm needs a large amount of data to train a deep model and guarantee the models ability to generalize. It...
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