• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.878-879
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• 2021

Most state-of-the-art CNNs for action recognition are based on a two-stream architecture: RGB frames stream represents the appearance and the optical flow stream interprets the motion of action. However, the cost of optical flow computation is very high and then it increases action recognition latency. We introduce a design strategy for action recognition inspired by a two-stream network and teacher-student architecture. There are two sub-networks in our neural networks, the optical flow sub-network as a teacher and the RGB frames sub-network as a student. In the training stage, we distill the feature from the teacher as a baseline to train student sub-network. In the test stage, we only use the student so that the latency reduces without computing optical flow. Our experiments show that its advantages over two-stream architecture in both speed and performance.

• Proceedings of the Korean Magnestics Society Conference
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• 2008.12a
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• pp.314.1-314.1
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• 2008

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.377-382
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• 2009

In this paper, theoretical analysis for metropolitan optical networks is performed. First, analytical optical SNR is derived assuming each node consists of an EDFA, an optical filter, an optical switch, and a VOA, and then the relationship between OSNR and BER is studied. In a metropolitan optical network, an optical signal can be dropped to deliver data, and we also studied the effect of drop loss on system performance. When the drop loss is relatively small, the receiver structure of the node can be treated as a preamplifier receiver which is widely used in long-haul systems. In that case, ASE noise from EDFAs is the dominant noise source in the receiver. However, system performance is relatively insensitive to OSNR when the drop loss is significant because of the noise sources in the receiver (thermal and shot noise).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.1-17
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• 2016

The separated management and operation of commercial IP/optical multilayer networks makes network operators look for a unified control plane (UCP) to reduce their capital and operational expenditure. Software-defined networking (SDN) provides a central control plane with a programmable mechanism, regarded as a promising UCP for future optical networks. The general control and scheduling mechanism in SDN-based optical burst switching (OBS) networks is insufficient so the controller has to process a large number of messages per second, resulting in low network resource utilization. In view of this, this paper presents the burst-flow scheduling mechanism (BFSM) with a proposed scheduling algorithm considering channel usage. The simulation results show that, compared with the general control and scheduling mechanism, BFSM provides higher resource utilization and controller performance for the SDN-based OBS network in terms of burst loss rate, the number of messages to which the controller responds, and the average latency of the controller to process a message.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.256-263
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• 2002

Optical Multistage Interconnection Networks(OMINs) comprising photonic switches have been studied extensively as important interconnecting building blocks for communication networks and parallel computing systems. A basic element of photonic switching networks is a 2$\times$2 directional coupler with two inputs and two outputs. This paper is concerned with the diagnosis of cross-talk-faults in OMINs. As the size of today's network becomes very large, the conventional diagnosis methods based on tests and simulation have become inefficient, or even more, impractical. In this paper, we propose a simple and easily implementable algorithm for detection and isolation of the single crosstalk-fault in OMINs. Specifically, we develope an algorithm fur the isolation of the source fault in switching elements whenever the single crosstalk-fault is detected in OMINS. The proposed algorithm is illustrated by an example of 16$\times$16 banyan network.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.286-297
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• 2011

A novel converged optical network unit (ONU)-base station (BS) architecture has been contemplated for next-generation optical-wireless networks. It has been demonstrated through high quality studies that data traffic carried by both wired and wireless networks exhibit self-similar and long range dependent characteristics; attributes that classical teletraffic theory based on simplistic Poisson models fail to capture. Therefore, in order to apprehend the proposed converged architecture and to reinforce the provisioning of tightly bound quality of service (QoS) parameters to end-users, we substantiate the analysis of the QoS behavior of the ONU-BS under self-similar and long range dependent traffic conditions using custom queuing which is a common queuing discipline. This paper extends our previous work on priority queuing and brings novelty in terms of presenting performance analysis of the converged ONU-BS under realistic traffic load conditions. Further, the presented analysis can be used as a network planning and optimization tool to select the most robust and appropriate queuing discipline for the ONU-BS relevant to the QoS requirements of different applications.

• Proceedings of the Optical Society of Korea Conference
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• 2003.02a
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• pp.246-247
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• 2003

In recent years, soaring traffic volumes over optical communications networks lead to the rapid advances in information communications equipments. In backbone communications networks, there has been an advance in high-density transmission through DWDM, which can simultaneously transmit numerous signals with different wavelengths. When the channel spacing is narrower, the cross-talk between channels an important parameter that guarantees to the high performance of a whole system, becomes critical. (omitted)

• The KIPS Transactions:PartC
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• v.10C no.4
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• pp.447-454
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• 2003

Optical burst switching (OBS) has been proposed to reduce the use of fiber delay lines (FDLs) and to realize the optical switching paradigm of the next-generation ail optical networks. The OBS can provide improvements over wavelength routing in terms of bandwidth efficiency and core network scalability via statistical multiplexing of bursts. Recently, another challenging issue is how to upport quality of service (QoS) in the optical burst switching networks. In this paper, we propose a deflection routing scheme to guarantee the QoS for the OBS networks to detour lower priority burst forward to the deflection routing path when congested. A big advantage of the proposed scheme is the simplicity of QoS provision, that comes from the simple QoS provisioning algorithm. Also, the QoS provisioning scheme be able to make efficient networks by fairly traffic distributing with the reduce of the use of FDLs at core routers. The QoS provisioning scheme has been verified to reliably guarantee the QoS of priority 0, 1, 2 burst and to efficiently utilize network resources by computer simulations using OPNET As results, the end-to-end delay of high priority burst is improved, and the network efficiency is also improved.

• Korean Journal of Optics and Photonics
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• v.24 no.4
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• pp.184-188
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• 2013

Two types of polymer-based optical splitters with $200{\mu}m$ large core are presented for optical multimode networks, such as smart home networks, intelligent automotive networks, etc. Optical splitters that have 1:1 symmetric and 9:1 asymmetric structure were fabricated by a ultra violet(UV)-imprint technology using a deep etched Si(silicon) master by the Bosch process. In this paper, we successfully fabricated the symmetric and asymmetric optical splitters with suitable optical network applications.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.48-56
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• 1995

This paper presents a method of implementing efficient optical flow estimation for dynamic scene analysis using the hierarchical Hopfield neural networks. Given the two consequent inages, Zhou and Chellappa suggested the Hopfield neural network for computing the optical flow. The major problem of this algorithm is that Zhou and Chellappa's network accompanies self-feedback term, which forces them to check the energy change every iteration and only to accept the case where the lower the energy level is guaranteed. This is not only undesirable but also inefficient in implementing the Hopfield network. The another problem is that this model cannot allow the exact computation of optical flow in the case that the disparities of the moving objects are large. This paper improves the Zhou and Chellapa's problems by modifying the structure of the network to satisfy the convergence condition of the Hopfield model and suggesting the hierarchical algorithm, which enables the computation of the optical flow using the hierarchical structure even in the presence of large disparities.