Sign language recognition using hybrid of Hog-Hu movement feature extraction techinques with RLO ensemble classifier /
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Format: | Thesis Book |
Language: | English |
Published: |
2018.
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LEADER | 01202cam a2200301 i 4500 | ||
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001 | u1096756 | ||
003 | SIRSI | ||
005 | 201810120935 | ||
008 | 181012s2018 my a m 000 0 eng | ||
040 | |a UMM |e rda | ||
090 | |a QA76.758 |b UM 2018 Emiar | ||
100 | 0 | |a Emir Afiq Ridzuan, |e author. | |
245 | 1 | 0 | |a Sign language recognition using hybrid of Hog-Hu movement feature extraction techinques with RLO ensemble classifier / |c Emir Afiq bin Ridzuan. |
264 | 1 | |c 2018. | |
300 | |a xv, 124 leaves : |b illustrations ; |c 30 cm. | ||
336 | |a text |2 rdacontent | ||
337 | |a unmediated |2 rdamedia | ||
338 | |a volume |2 rdacarrier | ||
502 | |b M.Comp.Sc. |c Jabatan Kejuruteraan Perisian, Fakulti Sains Komputer dan Teknologi Maklumat, Universiti Malaya |d 2018. | ||
504 | |a Bibliography: leaves 112-124. | ||
650 | 0 | |a Pattern perception. | |
650 | 0 | |a Pattern recognition systems. | |
650 | 0 | |a Human-computer interaction. | |
650 | 0 | |a Sign language. | |
710 | 2 | |a Universiti Malaya. |b Jabatan Kejuruteraan Perisian, |e degree granting institution. | |
596 | |a 1 | ||
900 | |a NSM | ||
999 | |a QA76.758 UM 2018 EMIAR |w LC |c 1 |i A517220698 |d 19/10/2018 |f 19/10/2018 |g 1 |l STACKS |m P01UTAMA |r Y |s Y |t TESIS |u 19/10/2018 |1 STEM |