{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T06:45:44Z","timestamp":1648795544507},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Artif. Intell. Tools"],"published-print":{"date-parts":[[1997,6]]},"abstract":"<jats:p> An automatic target recognition (ATR) classifier is constructed that uses a set of dedicated vector quantizers (VQs). The background pixels in each input image are properly clipped out by a set of aspect windows. The extracted target area for each aspect window is then enlarged to a fixed size, after which a wavelet decomposition splits the enlarged extraction into several subbands. A dedicated VQ codebook is generated for each subband of a particular target class at a specific range of aspects. Thus, each codebook consists of a set of feature templates that are iteratively adapted to represent a particular subband of a given target class at a specific range of aspects. These templates are then further trained by a modified learning vector quantization (LVQ) algorithm that enhances their discriminatory characteristics. <\/jats:p>","DOI":"10.1142\/s0218213097000098","type":"journal-article","created":{"date-parts":[[2003,10,22]],"date-time":"2003-10-22T09:26:17Z","timestamp":1066814777000},"page":"165-178","source":"Crossref","is-referenced-by-count":8,"title":["An Application of Wavelet-Based Vector Quantization in Target Recognition"],"prefix":"10.1142","volume":"06","author":[{"given":"Lipchen Alex","family":"Chan","sequence":"first","affiliation":[{"name":"Electrical and Computer Engineering, University at Buffalo, 201 Bell Hall, Buffalo, NY 14260-2050, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nasser M.","family":"Nasrabadi","sequence":"additional","affiliation":[{"name":"US Army Research Laboratory, ATTN: AMSRL-SE-SE, 2800 Powder Mill Road, Adelphi, MD 20783-1197, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"container-title":["International Journal on Artificial Intelligence Tools"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218213097000098","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T17:45:41Z","timestamp":1565199941000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218213097000098"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1997,6]]},"references-count":0,"journal-issue":{"issue":"02","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1997,6]]}},"alternative-id":["10.1142\/S0218213097000098"],"URL":"https:\/\/doi.org\/10.1142\/s0218213097000098","relation":{},"ISSN":["0218-2130","1793-6349"],"issn-type":[{"value":"0218-2130","type":"print"},{"value":"1793-6349","type":"electronic"}],"subject":[],"published":{"date-parts":[[1997,6]]}}}