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This paper describes an offline PC based system to classify normal and abnormal heart sound signals from heart sound audio files. The system reads the selected heart sound signal, automatically segments the heart sound signals into samples, extract the feature of each samples using cross-correlation method and classify the samples using the hierarchical multilayer perceptron network. Matlab GUI is...
Three-dimensional nerve information is required for the diagnosis of peripheral neuropathy. We have developed a prototype manipulating device and developed an algorithm for extracting peripheral nerves from the ultrasonic wave images captured using this probe and produce three-dimensional median nerve. Unlike the images captured by artificially manipulating the probe, the images captured by our device...
Visual Simultaneous Localization and Mapping (VSLAM) requires feature detection on visual data. In indoor scenes that include architectures such as plain walls and doors, there are no or less corners detected, in such cases tracking will be lost. To overcome this situation we track different types of features that help in feature extraction even in textureless scenes. Line features are used to get...
In general, the three main modules of color image classification systems are: color-to-grayscale image conversion, feature extraction and classification. The color-to-grayscale image conversion is the important pre-processing step which must incorporate the significant and discriminative contrast and structure information in the converted grayscale images as in the original color image. All the existing...
Bangla is one of the most widely used languages worldwide. This paper presents an application of image retrieval techniques to automatically judge the aesthetic quality of handwritten Bangla isolated characters. Retrieval techniques are also adapted to give improvement suggestions, with a plan to incorporate the methods in applications which can assist in learning/teaching handwriting. The proposed...
This paper is a combined method for stereo matching. Between the stereo images have difference perspective each other. The difference of stereo images is called disparity. This information measures the difference of reference and target stereo images. Then we can estimate the correspondence points on the target image from reference image. The proposed method is a combination of SIFT and cost aggregation...
Use of camera has increased among professionals and nonprofessionals in recent years and videos are being captured widely and wildly for information, knowledge, surveillance, adventures and memories. So these videos are highly vulnerable to suffer from translational and rotational noises. These noise are caused by multiple factors and it is difficult to remove all those causes. So digital video stabilization...
Many animal species exist in this world and there are always new species being discovered each year. Therefore, it is very important that these valuable species be documented properly to be referred to in future. Numerous information retrieval systems for managing and documenting animal species today only allow users to search animal images and descriptions online via text-based input. Therefore,...
The evolution of the Internet has created an abundance of unstructured data on the web, a significant part of which is textual. The task of author profiling seeks to find the demographics of people solely from their linguistic and content-based features in text. The ability to describe traits of authors clearly has applications in fields such as security and forensics, as well as marketing. Instead...
Saliency detection in images attracts much research attention for its usage in numerous multimedia applications. In this paper, we propose a saliency detection method based on optimization for RGBD images. With RGBD images, our method utilizes the depth channel to enhance the identification of background and foreground regions. We firstly generate new depth image by using non-linear transformation...
This paper presents a methodology for controlling the direction of motor taking a video sample from a camera as input. To control the direction the subject has to move his head in a direction which he would want the motor to rotate. The main challenge would be classifying the test sequence which has the data of the activity performed by the subject The actions are recognized in the frontal view by...
In order to reduce the false matching rate and matching time, an improved algorithm based on RANSAC-SIFT was proposed. The feature points were extracted by SIFT algorithm firstly. Then most of the mismatching points were eliminated according to the constraints that matching distances tend to be consistent. Finally the remaining points were regarded as pre matching points for achieve fine matching...
Most pedestrian detection algorithms only provide the object region instead of the actual body segmentation in video. For reducing the large number of redundant information and extracting a clear contour and texture feature of an up-right person, a superpixel segmentation algorithm with region correlation saliency analysis is proposed from coarse to fine cutting without any prior information. This...
As the complex workload scheduling and resource allocating mechanism in big data system, programmers' configuration error is one of the most typical root causes of unsuccessful termination of jobs, which can result in performance deterioration, availability degradation, resource inefficiency and user unsatisfactory. In this paper, we propose an approach called SD-Predictor, to predict misconfiguration-induced...
Single feature of pedestrian is difficult to accurately describe the target using traditional algorithms. A new reidentification algorithm combing global features and local features with different distance metric function is introduced. First, weighted color histogram feature for whole pedestrian is extracted and combined with Bhattacharyya distance to roughly recognize targets. Then pedestrians’...
In this paper, a high speed detection method of aircraft targets in remote sensing images is proposed based on proposal oriented FAST and adaptive matching of local invariant features. In order to reduce the search scope, the region of parking apron is extracted by region growing based on OTSU segmentation. Moreover, Binarized Normed Gradient (BING) and Spectral Residual Saliency (SRS) are applied...
In this paper, we present ResNet-based vehicle classification and localization methods using real traffic surveillance recordings. We utilize a MIOvision traffic dataset, which comprises 11 categories including a variety of vehicles, such as bicycle, bus, car, motorcycle, and so on. To improve the classification performance, we exploit a technique called joint fine-tuning (JF). In addition, we propose...
Facial expression recognition is a very active research topic due to its potential applications in the many fields such as human-robot interaction, human-machine interfaces, driving safety, and health-care. Despite of the significant improvements, facial expression recognition is still a challenging problem that wait for more and more accurate algorithms. This article presents a new model that is...
We investigate the problem of representing an entire video using CNN features for human action recognition. End-to-end learning of CNN/RNNs is currently not possible for whole videos due to GPU memory limitations and so a common practice is to use sampled frames as inputs along with the video labels as supervision. However, the global video labels might not be suitable for all of the temporally local...
A key challenge of facial expression recognition (FER) is to develop effective representations to balance the complex distribution of intra- and inter- class variations. The latest deep convolutional networks proposed for FER are trained by penalizing the misclassification of images via the softmax loss. In this paper, we show that better FER performance can be achieved by combining the deep metric...
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