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This paper proposes an entity recognition system in image documents recognized by OCR. The system is based on a graph matching technique and is guided by a database describing the entities in its records. The input of the system is a document which is labeled by the entity attributes. A first grouping of those labels based on a function score leads to a selected set of candidate entities. The entity...
Multi-script writer identification consists in identifying a person of a given text written in one script from the samples of the same person written in another script. The rationale behind this is that the writing style of an individual remains constant across different scripts. While this hypothesis may hold, recent results on a multi-script writer identification competition show that classical...
Scene recognition is an important and challenging task in computer vision. We propose an end-to-end pipeline by combing convolutional neural networks (CNNs) with explicit attention model to determine several meaningful regions of original images for scene recognition. In the proposed pipeline, the spatial transformer network is leveraged as the attention module, which can automatically learn the scales...
Human age estimation is an important research topic and can find its applications in such as commodity recommendation and security monitoring. The establishment of existing estimators basically follows a same pipeline, i.e., an estimator is built from a given training dataset like FG-NET and then evaluated on a holdout testing set to determine its effectiveness. In doing so, a usually-followed assumption...
Fish recognition and identification in an underwater environment are important research topics. In this study, several real-world underwater videos were collected to construct a fish category database for further fish recognition and identification. Recently, compressive sensing, using reconstruction algorithms to reconstruct a sparse signal, has been successfully applied to face recognition. Reconstruction...
In this paper we propose a publicly available static hand pose database called OUHANDS and protocols for training and evaluating hand pose classification and hand detection methods. A comparison between the OUHANDS database and existing databases is given. Baseline results for both of the protocols are presented.
Autoimmune diseases are a family of more than 80 chronic, and often disabling, illnesses that develop when underlying defects in the immune system lead the body to attack its own organs, tissues, and cells. Diagnosis of autoimmune pathologies is based on research and identification of antinuclear antibodies (ANA) through indirect immunofluorescence (IIF) method and is performed by analyzing patterns...
In this paper, we introduce a new color texture operator for natural texture classification, the Dominant and Minor Sum and Difference Histograms (DM-SDH) descriptor. The proposed approach allows to incorporate both color and texture information in order to enhance the texture discrimination performance. For this purpose, a vectorial representation of the image is used for the descriptor extraction...
Wearable Devices (WD) are systems designed to do a specific task, these system are embedded in daily life personal objects. Usual transducers in wearable devices involve accelerometers gyroscopes, cameras etc. In WD is required to design efficiently in terms of power. Therefore, a new trend incorporates acoustic transducer that does not need a power supply to sense. They are very cheap and easy to...
The use of micro expressions as a means to understand ones state of mind has received major interest owing to the rapid increase in security threats. The subtle changes that occur on ones face reveals one's hidden intentions. Recognition of these subtle intentions by humans can be challenging as this needs well trained people and is always a time consuming task. Automatic recognition of micro expressions...
Pattern recognition is one of the fundamental competencies associated with computational thinking and STEM education. Although much has been written to define computational thinking (CT), we argue that CT is a multi-faceted construct and specific aspects of CT (such as pattern recognition) should be examined. The purpose of this study is to conduct a systematic review of literature on pattern recognition...
The pattern recognition system for biometric identification, which was presented in this paper, used mathematical and statistical approaches such as Principal Component Analysis as a feature extraction method also Cross Validation and k-nearest neighbor with Euclidean metric distance for the classification method. The proposed recognition system used face and androgenic hair as biometric traits with...
We propose a Convolutional Neural Network model to learn spatial footstep features end-to-end from a floor sensor system for biometric applications. Our model's generalization performance is assessed by independent validation and evaluation datasets from the largest footstep database to date, containing nearly 20,000 footstep signals from 127 users. We report footstep recognition performance as Equal...
This work describes the design, implementation and validation of a virtual interactive tour around the University of Quindo by using augmented reality and applying evaluation methods about usability and user-centered design with the aim of improving the user experience, together with the consistency of this tool in its usage; in this case, in the university campus.
Demographic change in the next few years will lead to a pronounced disparity in generation distribution. Hence there is a need to develop intelligent systems to support and maintain the autonomy of the elderly at home. A high priority in this case assumes the preparation-free acquisition of vital signs and patient parameters in long-term monitoring systems to detect early changes or deterioration...
The skeleton is an efficient and complete shape descriptor often used for matching. However, existing skeleton-based shape matching methods are computationally intensive. To reduce the algorithmic complexity, we propose to exploit the natural hierarchy of the skeleton. The aim is to quantify the importance of skeleton branches to guide the shape matching algorithm, in order to match branches having...
Clustering is a fundamental tool for data analysis. Typically, all attributes of the data are used for clustering. However, if a set of attributes can be divided into meaningful subsets, it may be effective to cluster the data for each subset. In this paper, we propose a method for dividing the set of elements of feature vectors into meaningful subsets. Considering the dependencies between the elements,...
The effective factographic information retrieval problem has been investigated in the paper. The primary objective of this paper is to outline factographic information retrieval and new Lemma related to properties of factographic information retrieval. The special curriculum has been developed for the set competences. The curriculum contains specialized disciplines. These disciplines use factographic...
Historical documents are essentially formed of handwritten texts that exhibit a variety of perceptual environment complexities. The cursive and connected nature of text lines on one hand and the presence of artefacts and noise on the other hand hinder achieving plausible results using current image processing algorithm. In this paper, we present a new algorithm which we termed QTE (Query by Text Example)...
An innovative system is proposed for using mobile devices for remote recognition. When the user draws a pattern in the local browser, the pattern is transmitted to a remote server that immediately performs the recognition task and database search. The recognition system uses bidirectional associative memory (BAM) with artificial neural network technology. This study is based on the example of buying...
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