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Although the existing correlation filter based on trackers has appeared to be more excellent in the visual tracking problem, there is still tremendous space for the improvement of the tracking performance, especially in the occlusion situation which is often ignored due to the difficulty in detection and processing. In this paper, a scale-adaptive tracker is proposed to handle the case of occlusion...
In modern electronic warfare, it is a severe challenge for the Electronic Support Measure (ESM) system to realize the recognition of the threat radiation source, the modulation of the pulse repetition interval (PRI) is closely related to the function and application of the radar radiation source. Therefore, the recognition of PRI modulation is greatly significance to the identification of the threat...
Emotional recognition as the key technology in the field of emotion computing has received more and more attentions in applications such as human-computer interaction, medical-assisted diagnosis and multimedia intelligence recommendation, and it has important research and application value. EEG recognition based on EEG is a commonly used and effective method of emotion recognition. More and more scholars...
The inherent dependencies between visual elements and aural elements are crucial for affective video content analyses, yet have not been successfully exploited. Therefore, we propose a multimodal deep regression Bayesian network (MMDRBN) to capture the dependencies between visual elements and aural elements for affective video content analyses. The regression Bayesian network (RBN) is a directed graphical...
A major challenge in matching between vision and language is that they typically have completely different features and representations. In this work, we introduce a novel bridge between the modality-specific representations by creating a co-embedding space based on a recurrent residual fusion (RRF) block. Specifically, RRF adapts the recurrent mechanism to residual learning, so that it can recursively...
Recent approaches for high accuracy detection and tracking of object categories in video consist of complex multistage solutions that become more cumbersome each year. In this paper we propose a ConvNet architecture that jointly performs detection and tracking, solving the task in a simple and effective way. Our contributions are threefold: (i) we set up a ConvNet architecture for simultaneous detection...
Analysis of electrocardiogram and heart rate provides useful information about health condition of a patient. The North Sea Bicycle Race is an annual competition in Norway. Examination of ECG recordings collected from participants of this race may allow defining and evaluating the relationship between physical endurance exercises and heart electrophysiology. Parameters reflecting potentially alarming...
Resource usage data, collected using tools such as TACC_Stats, capture the resource utilization by nodes within a high performance computing system. We present methods to analyze the resource usage data to understand the system performance and identify performance anomalies. The core idea is to model the data as a three-way tensor corresponding to the compute nodes, usage metrics, and time. Using...
Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The Multi-Instance Multi-Label Learning (MIML) is an important type of machine learning framework proposed recently for IMC. In this framework, an image is described with...
A key issue in fruit export is classification and sorting for marketing. In this work image processing techniques are used to grad Thompson orange fruit. For this purpose, fourteen parameters were extracted, comprising area, eccentricity, perimeter, length/area, blue value, green value, red value, width, contrast, texture, width/area, width/length, roughness, and length. Adaptive neuro fuzzy inference...
Blind signal extraction is particularly attractive to solve signal mixture problems while only one or a few source signals are desired. Many desired biomedical signals exhibit distinct periods. A sequential method based on second order statistics is introduced in this paper. One can choose to recover one source signal or all signals in a specific order. The validity and performance of the proposed...
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...
Cucumber downy mildew is a kind of disease which spreads very fast and isdangerous, in order to prevent the disease, peoplealways spray plenty of pesticides indiscriminately. Accurate assessment of the level of cucumber downy mildew is very important to the disease prevention and control. In a cucumber growing season, this paper collected the typical cucumber downy mildew leaf samples, and developed...
News videos store a huge amount of information and are a source of historical archives. The amount of news data is growing rapidly and unpredictably, hence video indexing on news videos is a tedious job. Manual indexing even though effective, it is slow and most expensive for a massive volume of data. Content Based Indexing and Retrieval (CBIR) is a solution for this problem. Textual modality based...
Background modelling and subtraction is an essential component in motion analysis with wide range of applications in computer vision, whereas the task becomes more challenging in context of complex scenarios such as dynamic backgrounds. In this paper, we address the problem of modelling dynamic backgrounds in online tensor leaning framework. We use Tucker decomposition to model thespatio-temporal...
Lower limb bones or lower limb component related to the torso with pelvic ankle interference can be fractured. Fractures can be detected automatically take advantage x-ray images performed using feature extraction methods. Feature Extraction helpful to know existence and location of fracture with x-ray images. This research apply Gray Level Co-Occurrence Matrix (GLCM) and K-Means Clustering Algorithm...
Command extraction from human beings becomes easier for a machine if it can analyze the non verbal ways of communication such as emotions. This paper focuses on improving the efficiency of extracting emotion from human facial expression images. The features that were extracted in this experiment were obtained from JAFFE (Japanese Female Facial Expression) database which includes 213 images of different...
Grey Level Co-Occurrence matrix is one of the oldest techniques used for texture analysis. The Grey Level Co-Occurrence matrix has two important parameters i.e. distance and direction. In this paper various combinations of distance and directional angles used for GLCM calculation are analyzed in order to recognize certain patterned images based on their textural features. Patterns considered in this...
Wireless sensor networks (WSNs) have found many applications in building environment monitoring and energy management applications. However, WSN data is not completely reliable and hence its use in energy management has to be carefully considered. Experiments conducted on a WSN test bed monitoring a campus classroom highlight how sensor data is prone to errors, underlining the need to detect faulty...
Some improvements in the classification of masses in the breast are proposed in this paper. First, for the purpose of enriching the information concerning the shape of the mass, a new morphological feature is extracted. Then, the textural features of the region of interest (ROI) are extracted by combining the undecimated wavelet transform (UWT) and the gray level co-occurrence matrix (GLCM). Finally,...
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