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.
The micro-Doppler (m-D) feature is regarded as a unique characteristic for target recognition. Sparse recovery based approaches for m-D parameter estimation using the single measurement vector (SMV) model have shown their effectiveness recently. However, SMV only fits for narrowband m-D signals, and accurate parameters can hardly be estimated using SMV in strong noise. The signals with the same sparse...
Order-batching is a common practice in orderpicking» which can reduce the total picking time if the orders have many relevant in Multi-Shuttle Warehouse System. In this paper, the performance of different order-batching methods that are made up of one seed-order selection rule and one accompanying-order selection rule is investigated. A seed-order selection rule selects the first order (i.e. the seed...
We consider the problem of duplicate false targets discrimination for mainlobe jamming cancellation in multistatic radar. When using the existing method of the adaptive mainlobe jamming cancellation algorithm (AMJCA) to suppress mainlobe interferences, duplicate false targets appear under the situation where a jammer is not spatially coincide with or not close to a target. False targets of this type...
In order to improve the detection probability of range-spread targets in white Gaussian noise, a detector using waveform contrast is proposed based on multiple-pulse trains. Firstly, sliding cross correlation is utilized to eliminate the detrimental influence of range migration. Then, arithmetic mean algorithm is adopted to synthesize the final high-resolution range profiles (HRRPs). Finally, the...
In order to balance the number of outbound and inbound tasks of each aisle and improve the working efficiency of the multi-tier shuttle system, three principles of storage location assignment were put forward: the principle of minimum correlation degree, the principle of equalization of product items and the principle of equalization of tasks, which were expected to be followed when storing products...
This paper presents a methodology for reducing functional test time in subthreshold SoCs targeting ultra-low power (ULP) internet-of-things (IoT) devices. Due to their low operating speed and voltage, subthreshold SoCs require significantly longer time to test than traditional SoCs. The proposed method models trans-threshold correlations to allow high voltage, high speed testing while accurately predicting...
Diabetes is one of the most prevalent diseases worldwide, and hundreds of millions of patients are suffering from diabetes and its serious complications. Early detection and early treatment are urgent needed for clinical diagnosis of diabetics. In this work, we establish a gene coexpression network framework to identify biomarkers of transcripts with highly different gene coexpression patterns in...
The purpose of this study is to determine the sleep status of college students. 12 volunteers(mean ± SE: 22 ± 2 yr, 170 ± 10cm, 61 ± 16 kg) take part in the research. The sleep situation are got by the waistband sleep monitor system. The average heart rate of the whole night, the average breath rate of the whole night, bed time, get up time, onset latency, total sleep time are monitored. These important...
Load forecasting is the basis of the design and implementation of the control strategy of the combined cooling heating and power (CCHP) system, and the precision affects the comprehensive energy efficiency of the system directly. In this paper, the gray relational analysis method is used to indicate the strong coupling relationship among the loads of heating, cooling and electricity in the system...
When pathologists analyze the cytopathological assessment process, they firstly find the optimum focused region by moving the microscope table along the Z axis. Auto-focusing provides a better and more effective imaging by reducing the personality dependence on the microscope system. Various studies have been carried out in the literature to determine the optimum auto-focus function. The aim of the...
Image is usually taken for expressing some kinds of emotions or purposes, such as love, celebrating Christmas. There is another better way that combines the image and relevant song to amplify the expression, which has drawn much attention in the social network recently. Hence, the automatic selection of songs should be expected. In this paper, we propose to retrieve semantic relevant songs just by...
In this paper, we propose a cross-modal deep variational hashing (CMDVH) method for cross-modality multimedia retrieval. Unlike existing cross-modal hashing methods which learn a single pair of projections to map each example as a binary vector, we design a couple of deep neural network to learn non-linear transformations from image-text input pairs, so that unified binary codes can be obtained. We...
Resting State-fMRI represents an emerging and powerful tool to explore brain functional connectivity (FC) changes associated with neurologic disorders. Compared to activation/task-related fMRI, Resting State fMRI has the advantages such as (i) Blood oxygen level dependent (BOLD) fMRI signals are self-generated and independent of subject's performance during the task and (ii) a single dataset is sufficient...
Communication system commonly exists cochannel interference, which is the main reason why the accuracy of directions-of-arrival (DOAs) estimation is low especially in an alpha stable distribution noise environment. Though the second-order DOA estimation algorithms work well in Gaussian noise, while the methods based on fractional lower-order statistics may do well but which depend on much of apriori...
Free-head 3D gaze tracking outputs both the eye location and the gaze vector in 3D space, and it has wide applications in scenarios such as driver monitoring, advertisement analysis and surveillance. A reliable and low-cost monocular solution is critical for pervasive usage in these areas. Noticing that a gaze vector is a composition of head pose and eyeball movement in a geometrically deterministic...
In this paper, we investigate a weakly-supervised object detection framework. Most existing frameworks focus on using static images to learn object detectors. However, these detectors often fail to generalize to videos because of the existing domain shift. Therefore, we investigate learning these detectors directly from boring videos of daily activities. Instead of using bounding boxes, we explore...
Very large-scale Deep Neural Networks (DNNs) have achieved remarkable successes in a large variety of computer vision tasks. However, the high computation intensity of DNNs makes it challenging to deploy these models on resource-limited systems. Some studies used low-rank approaches that approximate the filters by low-rank basis to accelerate the testing. Those works directly decomposed the pre-trained...
Automatic image aesthetics rating has received a growing interest with the recent breakthrough in deep learning. Although many studies exist for learning a generic or universal aesthetics model, investigation of aesthetics models incorporating individual user’s preference is quite limited. We address this personalized aesthetics problem by showing that individual’s aesthetic preferences exhibit strong...
We propose a novel memory network model named Read-Write Memory Network (RWMN) to perform question and answering tasks for large-scale, multimodal movie story understanding. The key focus of our RWMN model is to design the read network and the write network that consist of multiple convolutional layers, which enable memory read and write operations to have high capacity and flexibility. While existing...
Correlation Filters (CFs) have recently demonstrated excellent performance in terms of rapidly tracking objects under challenging photometric and geometric variations. The strength of the approach comes from its ability to efficiently learn - on the fly - how the object is changing over time. A fundamental drawback to CFs, however, is that the background of the target is not modeled over time which...
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.