• Journal of KIISE:Software and Applications
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• v.32 no.12
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• pp.1260-1270
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• 2005

Support Vector Machines (SVM) is well known for a representative learner as one of the kernel methods. SVM which is based on the statistical learning theory shows good generalization performance and has been applied to various pattern recognition problems. However, SVM is basically to deal with a two-class classification problem, so we cannot solve directly a multi-class problem with a binary SVM. One-Per-Class (OPC) and All-Pairs have been applied to solve the face recognition problem, which is one of the multi-class problems, with SVM. The two methods above are ones of the output coding methods, a general approach for solving multi-class problem with multiple binary classifiers, which decomposes a complex multi-class problem into a set of binary problems and then reconstructs the outputs of binary classifiers for each binary problem. In this paper, we introduce the output coding methods as an approach for extending binary SVM to multi-class SVM and propose new output coding schemes based on the Error-Correcting Output Codes (ECOC) which is a dominant theoretical foundation of the output coding methods. From the experiment on the face recognition, we give empirical results on the properties of output coding methods including our proposed ones.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.795-801
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• 2013

Recently, support vector machine has been widely used in various application fields due to its superiority of classification performance comparing with decision tree and neural network. Since support vector machine is basically designed for the binary classification problem, output coding method to analyze the classification result of multiclass binary classifier is used for the application of support vector machine into the multiclass problem. However, previous feature selection method for output coding based support vector machine found the features to improve the overall classification accuracy instead of improving each classification accuracy of each classifier. In this paper, we propose the novel feature selection method to find the features for maximizing the classification accuracy of each binary classifier in output coding based support vector machine. Experimental result showed that proposed method significantly improved the classification accuracy comparing with previous feature selection method.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.51-57
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• 2020

Currently, High-efficient video coding (HEVC) has become the most promising video coding technology. However, the implementation of HEVC in video streaming systems is restricted by factors such as cost, design complexity, and compatibility with existing systems. While HEVC is considering deploying to various systems with different reached methods, H264/AVC can be one of the best choices for current video streaming systems. This paper presents an adaptive method for manipulating video streams using video coding on an integrated circuit (IC) designed with a private network processor. The proposed system allows to transfer multimedia data from cameras or other video sources to client. For this work, a series of video or audio packages from the video source are forwarded to the designed IC via HDMI cable, called Tx transmitter. The Tx processes input data into a real-time stream using its own protocol according to the Real-Time Transmission Protocol for both video and audio, then Tx transmits output packages to the video client though internet. The client includes hardware or software video/audio decoders to decode the received packages. Tx uses H264/AVC or HEVC video coding to encode video data, and its audio coding is PCM format. By handling the message exchanges between Tx and the client, the transmitted session can be set up quickly. Output results show that transmission's throughput can be achieved about 50 Mbps with approximately 80 msec latency.

• ETRI Journal
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• v.42 no.3
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• pp.341-350
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• 2020

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple-input multiple-output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space-time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple-input multiple-output (MIMO) data transmission technique in the WSNs. The DSC-MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC-MIMO scheme, energy consumption is lower than that in the CMIMO technique; it is also lower in the DSC single-input single-output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.

• Current Optics and Photonics
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• v.2 no.5
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• pp.407-412
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• 2018

An optimal matching approach is proposed to maximally ensure the output power uniformity of the cascaded encoder in the passive optical network (PON) monitoring system based on a remote coding scheme. The calculation results show that the optimum arrangement can effectively reduce the difference of the total insertion loss in comparison to the random arrangement (i.e., 0.07 dB vs 2.67 dB in the cascaded encoder with 16 output ports). The proposed approach realizes the optimum configuration for the $1{\times}2$ optical splitters used without adding any extra components. The test results of the fabricated cascaded encoder with 32 output ports prove the feasibility of the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.984-986
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• 1989

101 coding scheme, one of sliding block coding techniques, provides practically attractive features in some compression applications for image sources such as facsimile. This paper presents a new simple model of 101 coder. The results show that the entropy of the output of the 101 coder can be reduced close to the rate distortion bound of a binary first-order markov source.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.152-160
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• 2012

This paper proposes a frame-level rate control algorithm for low delay video applications to reduce the fluctuations in the bitrate. The proposed algorithm minimizes the bitrate fluctuations in two ways with minimal coding loss. First, the proposed rate control applies R-Q model to all frames including the first frame of every group of pictures (GOP) except for the first one of a sequence. Conventional rate control algorithms do not use any R-Q models for the first frame of each GOP and do not estimate the generated-bit. An unexpected output rate result from the first frame affects the remainder of the pictures in the rate control. Second, a rate-distortion (R-D) cost is calculated regardless of the hierarchical coding structure for low bitrate fluctuations because the hierarchical coding structure controls the output bitrate in rate distortion optimization (RDO) process. The experimental results show that the average variance of per-frame bits with the proposed algorithm can reduce by approximately 33.8% with a delta peak signal-to-noise ratio (PSNR) degradation of 1.4dB for a "low-delay B" coding structure and by approximately 35.7% with a delta-PSNR degradation of 1.3dB for a "low-delay P" coding structure, compared to HM 8.0 rate control.

• Smart Media Journal
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• v.1 no.2
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• pp.6-11
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• 2012

In the HEVC standard, transform coefficient coding that affects the output bitstream directly is a core part of the encoder and it includes coefficient scanning and entropy coding. Recently, JCT-VC(Joint Collaborative Team on Video Coding) advances to HEVC Committee Draft (CD). In this paper, we explain HEVC transform coefficient coding and propose an efficient transform coefficient coding method considering statistics of transform coefficients in the intra frame coder. The proposed method reduces BD-Rate by up to 0.74%, compared to the conventional HEVC transform coefficient coding.

• Journal of Communications and Networks
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• v.12 no.1
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• pp.11-18
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• 2010

Diversity-multiplexing tradeoff (DMT) is an efficient tool to measure the performance of multiple-input and multiple-output (MIMO) systems and cooperative systems. Recently, cooperative multicast system with wireless network coding stretched tremendous interesting due to that it can drastically enhance the throughput of the wireless networks. It is desirable to apply DMT to the performance analysis on the multicast system with wireless network coding. In this paper, DMT is performed at the three proposed wireless network coding protocols, i.e., non-regenerative network coding (NRNC), regenerative complex field network coding (RCNC) and regenerative Galois field network coding (RGNC). The DMT analysis shows that under the same system performance, i.e., the same diversity gain, all the three network coding protocols outperform the traditional transmission scheme without network coding in terms of multiplexing gain. Our DMT analysis also exhibits the trends of the three network coding protocols' performance when multiplexing gain is changing from the lower region to the higher region. Monte-Carlo simulations verify the prediction of DMT.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.437-447
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• 2006

Error Correcting Output Coding(ECOC) is used to solve multi-class problem. It is known that it improves the classification accuracy. In this paper, we compared various criteria to design code matrix while encoding. In addition. we prorpose an ensemble which uses the ability of each classifier while decoding. We investigate the justification of the proposed method through real data and synthetic data.