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Recently, very deep convolutional neural networks (CNNs) have been attracting considerable attention in image restoration. However, as the depth grows, the longterm dependency problem is rarely realized for these very deep models, which results in the prior states/layers having little influence on the subsequent ones. Motivated by the fact that human thoughts have persistency, we propose a very deep...
In this work, we address the human parsing task with a novel Contextualized Convolutional Neural Network (Co-CNN) architecture, which well integrates the cross-layer context, global image-level context, within-super-pixel context and cross-super-pixel neighborhood context into a unified network. Given an input human image, Co-CNN produces the pixel-wise categorization in an end-to-end way. First,...
Architecture of fast data recovery was introduced into the design of the digital receiver in UHF RFID Reader. The data should be recovered in a short time for the next step of decoding. Rich synchronizing information in Miller coding was used to improve the quality of decoding in a poor situation. The architecture of fast data recovery consisted of edge detector, period measure, cnt_syn and data recovery...
Recent years have witnessed phenomenal growth in the number of internet multimedia documents, such as un-annotated scene images. Image concept detection is an important step for image query. In this paper, we tackle the problem of image concept detection, namely automatically detecting concepts in an un-annotated image. In fact, a scene image always contains multiple concepts. In order to detect all...
Multi-concept image query is a multi-label classification challenge. Traditional query methods focus on single concept query, and only use image visual data without considering the associated textual tag data. In this work, we address the problem of bimodal multi-concept image query, namely retrieving bimodal images with multiple target concepts from the image set. We propose a novel Bimodal Learning...
During the past few years, there has been a massive explosion of multimedia content such as un-annotated images on the web. Automatic image annotation is an important task for multimedia retrieval. By automatically allocating semantic concepts to un-annotated images, image retrieval can be performed over annotation concepts. In this work, we address the problem of automatic image annotation, namely...
Recognition of outer membrane proteins (OMPs) from non-OMPs (global protein or inner protein) is one of the most important tasks in the field of computational biology and bioinformatics. Successful discrimination of OMPs from other types of proteins would help to identify new OMPs for biological applications. In this article, protein sequence index (PSI) and dipeptide motifs were applied to recognize...
Speech time series are manifolds in high dimensional feature space. The models of Speech recognition are to reflect the characteristics of the feature space distribution of time series manifolds. Each state in Hidden Markov Model (HMM) corresponds to an area in feature space, and the number of states in model corresponds to time sampling accuracy of manifolds in a higher level. From time and space...
Based on the product design characteristics of small- and medium-sized industry enterprises, this paper presents a novel crowdsourcing based business management model to enhance innovation design services for them to speed up the grow-up of enterprises. It builds on a crowdsourcing-based network service platform, which integrates the design requirements of enterprises with the designers (witkeys)...
A GaN-based light emitting diode (LED) with InGaN/GaN/InGaN multi-layer barrier (MLB) is studied. Simulation results show that GaN-based LED with MLB has better performance than conventional GaN-based LED with only one GaN barrier, which we found is due to enhancement of hole injection into quantum well and decrease of electron current leakage.
Marketing strategy has switch to the experience stage from the value stage and brand stage. Experience demand of the internet brand can be divided five types, sensory experience, emotional experience, thinking experience, behavioral experience, conjunctive experience, and the corresponding five experience design constitute one system of internet brand design based on experience demand.
An innovative system of supercritical water oxidation with a transpiring wall reactor was designed and constructed. Temperature fields inside the reactor, the contents of gas effluent, total organic carbon (TOC) removal efficiency and energy utilization efficiency of supercritical water oxidation of glucose were investigated at different feed flow rates. Higher reaction temperature, longer useful...
On the research of the postgraduate specialty curriculum arrangement of instructional technology, United States has taken the leading position in the world, mainly developed postgraduate education, and made the long-term exploration and practice. So this paper detailedly surveys the postgraduate specialty curriculum arrangement of instructional technology in 14 American universities. According to...
This paper explains some of the ideals and characters about PLE (personal learning environment). And introduce web2.0 social software and technology to construct PLE, where there is the difficulty for learners to integrate these dispersive tools and technologies. So it proposes a framework for an open source Personal Learning Environment which is called PLEF. The emphasis is on the process to build...
The technique of planer laser induced fluorescence (PLIF) is applied to measure the water temperature. The fluorescence dye, Rhodamine B, is used as the temperature indicator. Experimental results show that two spectral bands, in the ranges of 572.2-573.1 nm and 597.6-607.5 nm, can be selected for their strong difference in the intensity of the fluorescence quantum yield. Thus, the ratio of these...
Based on auto-correlated corner algorithm, we proposed a new method for pretreatment of speech signal in speech recognition system. The algorithm deleted semblable frames of speech signals which got after LPCC algorithm and MEL cepstrum transformation., and then solved characteristic redundancy efficiently. At last, we used speech recognition system based on spots-covering neural network to prove...
This paper proposes a new approach for speaker-independent continuous Chinese digit speech recognition based on multi-weighted neural network. By analyzing the geometrical meaning of the multi-weighted neuron function and on the principle of continuity point of view, this approach constructs a multi-weighted neural network. This network shows better recognition results when applied in digit speech...
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