IEEE Trans Image Process - Parametric generalized linear system based on the notion of the t-norm.

Tópicos

{ imag(2830) propos(1344) filter(1198) }
{ estim(2440) model(1874) function(577) }
{ take(945) account(800) differ(722) }
{ featur(1941) imag(1645) propos(1176) }
{ method(2212) result(1239) propos(1039) }
{ design(1359) user(1324) use(1319) }
{ data(3963) clinic(1234) research(1004) }
{ signal(2180) analysi(812) frequenc(800) }
{ method(1969) cluster(1462) data(1082) }
{ model(3404) distribut(989) bayesian(671) }
{ bind(1733) structur(1185) ligand(1036) }
{ patient(2315) diseas(1263) diabet(1191) }
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{ method(1557) propos(1049) approach(1037) }
{ general(901) number(790) one(736) }
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{ studi(1119) effect(1106) posit(819) }
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{ network(2748) neural(1063) input(814) }
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{ framework(1458) process(801) describ(734) }
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{ perform(999) metric(946) measur(919) }
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{ perform(1367) use(1326) method(1137) }
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{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
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{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
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{ health(1844) social(1437) communiti(874) }
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{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

By using the triangular norm, we propose two methods for the construction of generalized linear systems, and show new insights into the relationship between typical systems. Using the Hamacher and Frank t-norm, we propose a parametric log-ratio model, which is a generalization of the log-ratio model and is more flexible in algorithmic development. We develop a generalized linear contrast enhancement algorithm based on the proposed parametric log-ratio model. We show that the performance of the proposed algorithm is effective and robust for different types of images.

Resumo Limpo

use triangular norm propos two method construct general linear system show new insight relationship typic system use hamach frank tnorm propos parametr logratio model general logratio model flexibl algorithm develop develop general linear contrast enhanc algorithm base propos parametr logratio model show perform propos algorithm effect robust differ type imag

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