The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper introduces a complete heartbeat classification system based on modified stacked denoising autoencoders and neural networks. This system includes three parts and they are preprocessing, feature extraction, and classification. In the preprocessing part, the original ECG signal is filtered and segmented as each single heartbeat. In the feature extraction part, the features are extracted from...
Due to its low storage cost and fast query speed, cross-modal hashing (CMH) has been widely used for similarity search in multimedia retrieval applications. However, most existing CMH methods are based on hand-crafted features which might not be optimally compatible with the hash-code learning procedure. As a result, existing CMH methods with hand-crafted features may not achieve satisfactory performance...
In this work we pursue a data-driven approach to the problem of estimating surface normals from a single intensity image, focusing in particular on human faces. We introduce new methods to exploit the currently available facial databases for dataset construction and tailor a deep convolutional neural network to the task of estimating facial surface normals in-the-wild. We train a fully convolutional...
This paper described an active hand rehabilitation training system. This system is an active system designed in Unity3D platform and capture hands by Leap Motion. The system has the feature as amusement, sustainability and feedback. It can improve the movement and cognition ability. It set one to three level for different patient. And patient can grasp the different object and move to the certain...
Synthetic Aperture Radar (SAR) image land cover classification is an important task in SAR image interpretation. Supervised learning, such as Convolutional Neural Network (CNN), demands instances which are accurately labeled. However, a large amount of accurately labeled SAR images are difficult to produce. In this paper, a Probability Transition CNN (PTCNN) is proposed for patch-level SAR image land...
This paper introduces an approach to recognize face from 3D space on 2D image using fuzzy vector manifolds and nearest distance. We employ fuzzy vector to help the system minimize negative effect coming from noise and image degradation. On the training set, crisp vector representation of images will be transformed to its fuzzy vector representation using a specific triangle fuzzification method. Then,...
Palm vein recognition is developing biometric identification technology. It can be used in physical security and information security for selective control of access to a place or resource. A palm vein recognition has been gaining research interest from last few years because it use physiological intrinsic that uniqueness, stability, not easily spoofed and damaged and have live body identification...
Pedestrian detection is one of the key technologies in automotive safety, robotic and intelligent video surveillance. Recently, deep convolutional neural networks have achieved significant effect in image classification and retrieval tasks. In this paper, we propose a novel deep convolutional neural networks model for pedestrian detection to simultaneously extract and classify pedestrian features...
Music emotions recognition (MER) is a challenging field of studies addressed in multiple disciplines such as musicology, cognitive science, physiology, psychology, arts and affective computing. In this paper, music emotions are classified into four types known as those of pleasing, angry, sad and relaxing. MER is formulated as a classification problem in cognitive computing where 548 dimensions of...
Data mining can find some interest information from large amounts of data. Data association (association rules) can find associations among data items. Data classification distinguishes every data from a data set or group, and it also can combine data association. Formal concept analysis is a data analyzing theory which discovers concept structure in data sets. It can transform formal context into...
We introduce a data-driven approach to complete partial 3D shapes through a combination of volumetric deep neural networks and 3D shape synthesis. From a partially-scanned input shape, our method first infers a low-resolution – but complete – output. To this end, we introduce a 3D-Encoder-Predictor Network (3D-EPN) which is composed of 3D convolutional layers. The network is...
This paper proposes a novel approach for visual query compression with a bank of transforms selected on Grassmann manifold. Instead of using single transform and quantization pipeline for all the features extracted from an image, we group the key point features according to their local embedding subspace geometry and organize them into different leaf nodes of a KD-Tree which was built from a large...
The goal of image quality assessment (IQA) is to use computational models to measure the consistency between image quality and subjective evaluations. In recent years, convolutional neural networks (CNNs) have been widely used in image processing community and have achieved performance leaps than non CNNs-based methods. In this work, we describe an accurate deep CNNs model for no-reference IQA. Taking...
Nowadays the CNN is widely used in practical applications for image classification task. However the design of the CNN model is very professional work and which is very difficult for ordinary users. Besides, even for experts of CNN, to select an optimal model for specific task may still need a lot of time (to train many different models). In order to solve this problem, we proposed an automated CNN...
The aim of this work is to explore the usefulness of face semantic segmentation for head pose estimation. We implement a multi-class face segmentation algorithm and we train a model for each considered pose. Given a new test image, the probabilities associated to face parts by the different models are used as the only information for estimating the head orientation. A simple algorithm is proposed...
We propose the Component Bio-Inspired Feature (CBIF) with a moving segmentation scheme for age estimation. The CBIF defines a superset for the commonly used Bio-Inspired Feature (BIF) with more parameters and flexibility in settings, resulting in features with abundant characteristics. An in-depth study is performed for the determination of the parameters good for capturing age-related traits. The...
The purpose of data mining is to explore, find and hence analyze relevant data from a massive data source using various technical means. This paper introduces the development of data mining to date, its functions, tasks and algorithms, as well as the process of data mining. The application and problems of data mining are also presented and finally the potential future development of data mining technology...
This paper tackles the problem of reconstructing 3D human poses from 2D landmarks, which is still an ill-posed problem. A widely-used approach is active shape model (ASM) which considers an unknown 3D shape as a linear combination of predefined basis shapes. The existing methods often resolve an optimization problem to reckon the weights and viewpoints of basis shapes, but they could fall into a locally-optimal...
Collaborative representation based classifier (CRC) and its probabilistic improvement ProCRC have achieved satisfactory performance in many image classification applications. They, however, do not comprehensively take account of the structure characteristics of the training samples. In this paper, we present an extended probabilistic collaborative representation based classifier (EProCRC) for image...
Recent years have witnessed a growing interest in developing automatic parking systems in the field of intelligent vehicle. However, how to effectively and efficiently locating parking-slots using a vision-based system is still an unresolved issue. In this paper, we attempt to fill this research gap to some extent and our contributions are twofold. Firstly, to facilitate the study of vision-based...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.