Dong-Hoon Ahn

Learn More
Decoding in a precompiled static network, compared with one in a dynamically managed network, is easier to implement and faster enough to yield a near real time response. However, when the recognition system handles a complex task, it has a problem of intensive memory usage. To overcome this weakness, we present a new decoding strategy that combines the(More)
We have investigated the effects of sputtering Ar gas pressure on magnetic and magneto-optical properties in compositionally modulated Co/Pd thin films. The samples were prepared by dc magnetron sputtering from 2-in.-diam Co and Pd targets by alternately exposing the substrates to targets. Sputtering Ar gas pressure was varied from 2 to 30 mTorr. All(More)
We present an improved method of compactly organizing the decoding network for a semi-dynamic network decoder. In the previous work [1], the network management units called subnetworks were made compact by self-structuring themselves. We improve this subnetwork representation in two aspects by employing the shared-tail topology [2]. Firstly, we localize the(More)
In this paper, we present an improved semi-dynamic network decoding strategy by incorporating weighted finite-state transducer (WFST)-based search network. In our approach, a static search network is first optimized by applying WFST algorithms (determinization and minimization) to the composition of a lexicon and a language model. Then the WFST is(More)
  • 1