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Convolutional neural network (CNN) has become a successful algorithm in the region of artificial intelligence and a strong candidate for many computer vision algorithms. But the computation complexity of CNN is much higher than traditional algorithms. With the help of GPU acceleration, CNN-based applications are widely deployed in servers. However, for embedded platforms, CNN-based solutions are still...
Sparsity helps reducing the computation complexity of DNNs by skipping the multiplication with zeros. The granularity of sparsity affects the efficiency of hardware architecture and the prediction accuracy. In this paper we quantitatively measure the accuracy-sparsity relationship with different granularity. Coarse-grained sparsity brings more regular sparsity pattern, making it easier for hardware...
Convolutional neural networks (CNNs) have recently broken many performance records in image recognition and object detection problems. The success of CNNs, to a great extent, is enabled by the fast scaling-up of the networks that learn from a huge volume of data. The deployment of big CNN models can be both computation-intensive and memory-intensive, leaving severe challenges to hardware implementations...
For the problem of online thrust estimation difficulty in aero-engine direct control and health management, the aero-engine thrust estimation method is proposed based on the extreme learning machine. In order to reduce the online computation cost and ensure the sufficient accuracy, the correlation analysis method is used for selecting the input feature parameters. The number of neural network hidden...
The ability to estimate performance metrics such as latency (delay) at an early stage of final implementation in any embedded system is essential for efficient design specially realtime systems. Constructing performance models and evaluation techniques of a given system requires a significant effort. This paper presents a mapping scheme between a Functional Modeling Approach such as FSM, UML etc and...
The great availability of massively parallel computing platforms gives rise a question to the EDA industry-how can this be really helping the productivity of circuit designs. Scalability of traditional parallel methods have shown to be limited as the computational resources keep increasing. In this paper we propose a time-domain segmentation method for massively parallel transistor-level simulation...
This paper focuses on the task of recovering the neutral 3D face of a person when given his/her 3D face model with facial expression. We propose a learning-based expression removal framework to tackle this task. Our basic idea is to model expression residue from samples, and then use the inferred expression residue from the input expressional face model to recover the neutral one. A two-step non-rigid...
Cognitive Radio (CR) has been considered as a promising concept for improving the utilization of limited radio spectrum resources for future wireless communications and mobile computing. As cognitive radio network (CRN) is a general wireless heterogeneous network, it is very essential for detecting the misbehaving or false nodes in the network. So in this paper we propose a trust aware model which...
In this paper, we study the role of query recommendation on mobile search engine. We start with the discussion of the role of query recommendation in modern search engines. Secondly, a mobile search engine, Roboo?? (http://wap.roboo.com), is introduced and we discuss the need for query recommendation over mobile search engine. Thirdly, the query recommendation solution working on Roboo?? is introduced...
WirelessHART is an emerging wireless communication standard that is targeted at the real-time process control industry.An example application of wireless communication in an industrial process control plant is the location of field engineers. The capability to locate personnel is a safety critical issue in process control plants because of high risks posed by toxic chemicals and other hazards. This...
Self-healing key distribution schemes enable a group user to recover session keys from two broadcast messages it received before and after those sessions, even if broadcast messages for middle sessions are lost due to network failure. These schemes are quite suitable for supporting secure communication over unreliable networks such as sensor networks and ad hoc networks. An efficient self-healing...
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