{"id":477177,"date":"2023-08-09T09:08:44","date_gmt":"2023-08-09T09:08:44","guid":{"rendered":""},"modified":"2023-09-05T11:14:14","modified_gmt":"2023-09-05T11:14:14","slug":"facial-recognition","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/facial-recognition\/","title":{"rendered":"Nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t"},"content":{"rendered":"

Nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t l\u00e0 c\u00f4ng ngh\u1ec7 sinh tr\u1eafc h\u1ecdc \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh ho\u1eb7c x\u00e1c minh danh t\u00ednh c\u1ee7a m\u1ed9t ng\u01b0\u1eddi b\u1eb1ng khu\u00f4n m\u1eb7t c\u1ee7a h\u1ecd. N\u00f3 n\u1eafm b\u1eaft, ph\u00e2n t\u00edch v\u00e0 so s\u00e1nh c\u00e1c m\u1eabu d\u1ef1a tr\u00ean chi ti\u1ebft khu\u00f4n m\u1eb7t c\u1ee7a ng\u01b0\u1eddi \u0111\u00f3. N\u00f3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng trong nhi\u1ec1u \u1ee9ng d\u1ee5ng, bao g\u1ed3m h\u1ec7 th\u1ed1ng b\u1ea3o m\u1eadt, b\u1ea3o m\u1eadt di \u0111\u1ed9ng, ph\u01b0\u01a1ng ti\u1ec7n truy\u1ec1n th\u00f4ng x\u00e3 h\u1ed9i, v.v.<\/p>\n

L\u1ecbch s\u1eed c\u1ee7a nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t<\/h2>\n

\u00dd t\u01b0\u1edfng v\u1ec1 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t c\u00f3 t\u1eeb nh\u1eefng n\u0103m 1960 khi Woodrow Wilson Bledsoe ph\u00e1t tri\u1ec3n m\u1ed9t h\u1ec7 th\u1ed1ng c\u00f3 kh\u1ea3 n\u0103ng ph\u00e2n lo\u1ea1i \u1ea3nh khu\u00f4n m\u1eb7t theo c\u00e1ch th\u1ee7 c\u00f4ng b\u1eb1ng m\u00e1y t\u00ednh b\u1ea3ng RAND, m\u1ed9t thi\u1ebft b\u1ecb c\u00f3 th\u1ec3 nh\u1eadn d\u1ea1ng c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m c\u1ee7a con ng\u01b0\u1eddi. Tuy nhi\u00ean, ph\u1ea3i \u0111\u1ebfn nh\u1eefng n\u0103m 1970, c\u00e1c k\u1ef9 thu\u1eadt t\u00ednh to\u00e1n \u0111\u1ea7u ti\u00ean v\u1ec1 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t m\u1edbi \u0111\u01b0\u1ee3c kh\u00e1m ph\u00e1.<\/p>\n

C\u00f4ng ngh\u1ec7 n\u00e0y \u0111\u00e3 ch\u1ee9ng ki\u1ebfn s\u1ef1 ph\u00e1t tri\u1ec3n \u0111\u00e1ng k\u1ec3 v\u00e0o nh\u1eefng n\u0103m 2000, \u0111\u01b0\u1ee3c \u0111\u00e1nh d\u1ea5u b\u1eb1ng s\u1ef1 ra \u0111\u1eddi c\u1ee7a ph\u01b0\u01a1ng ph\u00e1p Eigenfaces, m\u1ed9t c\u00e1ch ti\u1ebfp c\u1eadn th\u00e0nh c\u00f4ng \u0111\u1ec3 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t trong h\u00ecnh \u1ea3nh, do Matthew Turk v\u00e0 Alex Pentland d\u1eabn \u0111\u1ea7u. Sau \u0111\u00f3, v\u00e0o n\u0103m 2001, vi\u1ec7c s\u1eed d\u1ee5ng nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t 3D \u0111\u00e3 \u0111\u01b0\u1ee3c gi\u1edbi thi\u1ec7u, gi\u00fap gi\u1ea3i quy\u1ebft c\u00e1c v\u1ea5n \u0111\u1ec1 v\u1ec1 thay \u0111\u1ed5i \u00e1nh s\u00e1ng v\u00e0 v\u1ecb tr\u00ed c\u1ee7a khu\u00f4n m\u1eb7t trong h\u00ecnh \u1ea3nh.<\/p>\n

Th\u00f4ng tin chi ti\u1ebft v\u1ec1 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t<\/h2>\n

Nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t l\u00e0 m\u1ed9t t\u1eadp h\u1ee3p con c\u1ee7a c\u00f4ng ngh\u1ec7 nh\u1eadn d\u1ea1ng sinh tr\u1eafc h\u1ecdc s\u1eed d\u1ee5ng c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m sinh l\u00fd \u0111\u1ed9c \u0111\u00e1o \u0111\u1ec3 nh\u1eadn d\u1ea1ng. N\u00f3 ho\u1ea1t \u0111\u1ed9ng d\u1ef1a tr\u00ean c\u00e1c nguy\u00ean t\u1eafc th\u1ecb gi\u00e1c m\u00e1y t\u00ednh, nh\u1eadn d\u1ea1ng m\u1eabu v\u00e0 h\u1ecdc m\u00e1y \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh ho\u1eb7c x\u00e1c minh m\u1ed9t c\u00e1 nh\u00e2n t\u1eeb h\u00ecnh \u1ea3nh k\u1ef9 thu\u1eadt s\u1ed1 ho\u1eb7c khung h\u00ecnh video.<\/p>\n

C\u00f4ng ngh\u1ec7 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t qu\u00e9t khu\u00f4n m\u1eb7t \u0111\u1ec3 thi\u1ebft l\u1eadp ch\u1eef k\u00fd tr\u00ean khu\u00f4n m\u1eb7t \u2013 m\u1ed9t c\u00f4ng th\u1ee9c to\u00e1n h\u1ecdc bi\u1ec3u th\u1ecb s\u1ef1 \u0111\u1ed9c \u0111\u00e1o trong c\u1ea5u tr\u00fac khu\u00f4n m\u1eb7t c\u1ee7a m\u1ed9t ng\u01b0\u1eddi. N\u00f3 th\u01b0\u1eddng nh\u00ecn v\u00e0o c\u00e1c \u0111i\u1ec3m n\u00fat ho\u1eb7c c\u00e1c \u0111i\u1ec3m m\u1ed1c c\u00f3 th\u1ec3 ph\u00e2n bi\u1ec7t nh\u01b0 kho\u1ea3ng c\u00e1ch gi\u1eefa hai m\u1eaft, chi\u1ec1u r\u1ed9ng c\u1ee7a m\u0169i, \u0111\u1ed9 s\u00e2u c\u1ee7a h\u1ed1c m\u1eaft, h\u00ecnh d\u1ea1ng c\u1ee7a x\u01b0\u01a1ng g\u00f2 m\u00e1 v\u00e0 chi\u1ec1u d\u00e0i c\u1ee7a \u0111\u01b0\u1eddng vi\u1ec1n h\u00e0m.<\/p>\n

C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t<\/h2>\n

C\u00f4ng ngh\u1ec7 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t bao g\u1ed3m nhi\u1ec1u giai \u0111o\u1ea1n:<\/p>\n

    \n
  1. Ph\u00e1t hi\u1ec7n<\/strong>: Nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t trong \u1ea3nh.<\/li>\n
  2. C\u0103n ch\u1ec9nh<\/strong>: \u0110i\u1ec1u ch\u1ec9nh khu\u00f4n m\u1eb7t \u0111\u01b0\u1ee3c ph\u00e1t hi\u1ec7n \u0111\u1ec3 c\u00f3 t\u01b0 th\u1ebf nh\u1ea5t qu\u00e1n.<\/li>\n
  3. Chu\u1ea9n h\u00f3a<\/strong>: \u0110i\u1ec1u ch\u1ec9nh v\u00e0 chia t\u1ef7 l\u1ec7 h\u00ecnh \u1ea3nh c\u1ee7a khu\u00f4n m\u1eb7t.<\/li>\n
  4. Bi\u1ec3u di\u1ec5n\/M\u00e3 h\u00f3a<\/strong>: Chuy\u1ec3n \u0111\u1ed5i d\u1eef li\u1ec7u khu\u00f4n m\u1eb7t th\u00e0nh m\u00e3 duy nh\u1ea5t (ch\u1eef k\u00fd khu\u00f4n m\u1eb7t).<\/li>\n
  5. K\u1ebft h\u1ee3p<\/strong>: So s\u00e1nh ch\u1eef k\u00fd khu\u00f4n m\u1eb7t v\u1edbi c\u00e1c khu\u00f4n m\u1eb7t \u0111\u00e3 bi\u1ebft trong c\u01a1 s\u1edf d\u1eef li\u1ec7u.<\/li>\n<\/ol>\n

    C\u00f4ng ngh\u1ec7 c\u01a1 b\u1ea3n t\u1eadn d\u1ee5ng tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o, \u0111\u1eb7c bi\u1ec7t l\u00e0 c\u00e1c thu\u1eadt to\u00e1n h\u1ecdc s\u00e2u nh\u01b0 m\u1ea1ng th\u1ea7n kinh t\u00edch ch\u1eadp (CNN), \u0111\u1ec3 \u0111\u00e0o t\u1ea1o tr\u00ean s\u1ed1 l\u01b0\u1ee3ng l\u1edbn khu\u00f4n m\u1eb7t v\u00e0 nh\u1eadn d\u1ea1ng c\u00e1c m\u1eabu.<\/p>\n

    C\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t<\/h2>\n

    C\u00f4ng ngh\u1ec7 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t cung c\u1ea5p m\u1ed9t s\u1ed1 t\u00ednh n\u0103ng \u0111\u1ed9c \u0111\u00e1o:<\/p>\n

      \n
    1. Qu\u00e1 tr\u00ecnh kh\u00f4ng ti\u1ebfp x\u00fac<\/strong>: C\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c th\u1ef1c hi\u1ec7n t\u1eeb xa.<\/li>\n
    2. Kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng cao<\/strong>: C\u00f3 th\u1ec3 x\u1eed l\u00fd m\u1ed9t l\u01b0\u1ee3ng l\u1edbn d\u1eef li\u1ec7u m\u1ed9t c\u00e1ch nhanh ch\u00f3ng.<\/li>\n
    3. Kh\u1ea3 n\u0103ng t\u00edch h\u1ee3p<\/strong>: C\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c t\u00edch h\u1ee3p v\u1edbi c\u00e1c h\u1ec7 th\u1ed1ng gi\u00e1m s\u00e1t hi\u1ec7n c\u00f3.<\/li>\n
    4. Nh\u1eadn d\u1ea1ng th\u1eddi gian th\u1ef1c<\/strong>: C\u00f3 kh\u1ea3 n\u0103ng nh\u1eadn d\u1ea1ng c\u00e1c c\u00e1 nh\u00e2n trong th\u1eddi gian th\u1ef1c.<\/li>\n<\/ol>\n

      C\u00e1c lo\u1ea1i nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t<\/h2>\n

      C\u00f3 nhi\u1ec1u lo\u1ea1i c\u00f4ng ngh\u1ec7 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t kh\u00e1c nhau, ch\u1ee7 y\u1ebfu \u0111\u01b0\u1ee3c ph\u00e2n bi\u1ec7t b\u1edfi k\u1ef9 thu\u1eadt ch\u00fang s\u1eed d\u1ee5ng:<\/p>\n

        \n
      1. Nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t truy\u1ec1n th\u1ed1ng ho\u1eb7c h\u00ecnh h\u1ecdc<\/strong>: S\u1eed d\u1ee5ng c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m h\u00ecnh h\u1ecdc c\u1ee7a m\u1ed9t khu\u00f4n m\u1eb7t.<\/li>\n
      2. Nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t 3D<\/strong>: Nh\u1eadn bi\u1ebft c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m trong kh\u00f4ng gian ba chi\u1ec1u.<\/li>\n
      3. Nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t nhi\u1ec7t<\/strong>: S\u1eed d\u1ee5ng h\u00ecnh \u1ea3nh nhi\u1ec7t \u0111\u01b0\u1ee3c ch\u1ee5p trong ph\u1ed5 h\u1ed3ng ngo\u1ea1i.<\/li>\n
      4. Ph\u00e2n t\u00edch k\u1ebft c\u1ea5u da<\/strong>: Ph\u00e2n t\u00edch c\u00e1c \u0111\u01b0\u1eddng, hoa v\u0103n v\u00e0 \u0111\u1ed1m tr\u00ean da c\u1ee7a m\u1ed9t ng\u01b0\u1eddi \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh khu\u00f4n m\u1eb7t.<\/li>\n<\/ol>\n\n\n\n\n\n\n\n\n
        Ki\u1ec3u<\/strong><\/th>\nK\u1ef9 thu\u1eadt \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng<\/strong><\/th>\nThu\u1eadn l\u1ee3i<\/strong><\/th>\nNh\u01b0\u1ee3c \u0111i\u1ec3m<\/strong><\/th>\n<\/tr>\n<\/thead>\n
        Truy\u1ec1n th\u1ed1ng<\/td>\n\u0110\u1eb7c \u0111i\u1ec3m h\u00ecnh h\u1ecdc<\/td>\n\u0110\u01a1n gi\u1ea3n, hi\u1ec7u qu\u1ea3 \u0111\u1ec3 nh\u1eadn d\u1ea1ng c\u01a1 b\u1ea3n<\/td>\nB\u1ecb \u1ea3nh h\u01b0\u1edfng b\u1edfi n\u00e9t m\u1eb7t, tu\u1ed5i t\u00e1c v\u00e0 \u00e1nh s\u00e1ng<\/td>\n<\/tr>\n
        3D<\/td>\nNh\u1eadn d\u1ea1ng 3D<\/td>\nCh\u1ecbu \u0111\u01b0\u1ee3c \u00e1nh s\u00e1ng, thay \u0111\u1ed5i t\u01b0 th\u1ebf<\/td>\nY\u00eau c\u1ea7u ph\u1ea7n c\u1ee9ng chuy\u00ean d\u1ee5ng<\/td>\n<\/tr>\n
        nhi\u1ec7t<\/td>\nPh\u1ed5 h\u1ed3ng ngo\u1ea1i<\/td>\nHo\u1ea1t \u0111\u1ed9ng trong \u0111i\u1ec1u ki\u1ec7n \u00e1nh s\u00e1ng y\u1ebfu, kh\u00f3 b\u1ecb \u0111\u00e1nh l\u1eeba<\/td>\n\u0110\u1eaft ti\u1ec1n, \u0111\u1ed9 ch\u00ednh x\u00e1c th\u1ea5p h\u01a1n<\/td>\n<\/tr>\n
        K\u1ebft c\u1ea5u da<\/td>\nPh\u00e2n t\u00edch da<\/td>\n\u0110\u1ed9 ch\u00ednh x\u00e1c cao, kh\u00f3 \u0111\u00e1nh l\u1eeba<\/td>\nPh\u1ee9c t\u1ea1p, c\u00f3 th\u1ec3 b\u1ecb \u1ea3nh h\u01b0\u1edfng b\u1edfi t\u00ecnh tr\u1ea1ng da<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        C\u00e1ch s\u1eed d\u1ee5ng, v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p<\/h2>\n

        C\u00f4ng ngh\u1ec7 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t c\u00f3 nhi\u1ec1u \u1ee9ng d\u1ee5ng bao g\u1ed3m th\u1ef1c thi ph\u00e1p lu\u1eadt, gi\u00e1m s\u00e1t, ki\u1ec3m so\u00e1t truy c\u1eadp, ti\u1ebfp th\u1ecb v\u00e0 truy\u1ec1n th\u00f4ng x\u00e3 h\u1ed9i. Tuy nhi\u00ean, n\u00f3 c\u0169ng \u0111\u1eb7t ra nh\u1eefng th\u00e1ch th\u1ee9c nh\u01b0 lo ng\u1ea1i v\u1ec1 quy\u1ec1n ri\u00eang t\u01b0, c\u00e1c v\u1ea5n \u0111\u1ec1 sai l\u1ec7ch ti\u1ec1m \u1ea9n v\u00e0 \u0111\u1ed9 ch\u00ednh x\u00e1c. C\u00e1c gi\u1ea3i ph\u00e1p bao g\u1ed3m lu\u1eadt ph\u00e1p \u0111\u1ec3 \u0111i\u1ec1u ch\u1ec9nh vi\u1ec7c s\u1eed d\u1ee5ng n\u00f3, c\u1ea3i ti\u1ebfn li\u00ean t\u1ee5c c\u00f4ng ngh\u1ec7 \u0111\u1ec3 gi\u1ea3m sai l\u1ec7ch v\u00e0 s\u1eed d\u1ee5ng c\u00e1c c\u00f4ng ngh\u1ec7 b\u1ed5 sung \u0111\u1ec3 c\u1ea3i thi\u1ec7n \u0111\u1ed9 ch\u00ednh x\u00e1c.<\/p>\n

        So s\u00e1nh v\u1edbi c\u00e1c c\u00f4ng ngh\u1ec7 sinh tr\u1eafc h\u1ecdc t\u01b0\u01a1ng t\u1ef1<\/h2>\n

        C\u00e1c c\u00f4ng ngh\u1ec7 sinh tr\u1eafc h\u1ecdc kh\u00e1c bao g\u1ed3m nh\u1eadn d\u1ea1ng v\u00e2n tay, nh\u1eadn d\u1ea1ng m\u1ed1ng m\u1eaft v\u00e0 nh\u1eadn d\u1ea1ng gi\u1ecdng n\u00f3i. M\u1eb7c d\u00f9 t\u1ea5t c\u1ea3 \u0111\u1ec1u ph\u1ee5c v\u1ee5 m\u1ee5c \u0111\u00edch x\u00e1c \u0111\u1ecbnh c\u00e1 nh\u00e2n, nh\u01b0ng \u0111\u1eb7c \u0111i\u1ec3m c\u1ee7a ch\u00fang kh\u00e1c nhau:<\/p>\n\n\n\n\n\n\n\n
        C\u00f4ng ngh\u1ec7 sinh tr\u1eafc h\u1ecdc<\/strong><\/th>\nT\u00ednh n\u0103ng \u0111\u1ed9c \u0111\u00e1o<\/strong><\/th>\nH\u1ea1n ch\u1ebf<\/strong><\/th>\n<\/tr>\n<\/thead>\n
        Nh\u1eadn d\u1ea1ng v\u00e2n tay<\/td>\n\u0110\u1ed9 ch\u00ednh x\u00e1c cao, c\u00f4ng ngh\u1ec7 tr\u01b0\u1edfng th\u00e0nh<\/td>\nC\u1ea7n ti\u1ebfp x\u00fac, b\u1ecb \u1ea3nh h\u01b0\u1edfng b\u1edfi b\u1ee5i b\u1ea9n<\/td>\n<\/tr>\n
        Nh\u1eadn d\u1ea1ng m\u1ed1ng m\u1eaft<\/td>\nC\u1ef1c k\u1ef3 ch\u00ednh x\u00e1c, kh\u00f3 gi\u1ea3 m\u1ea1o<\/td>\nY\u00eau c\u1ea7u kho\u1ea3ng c\u00e1ch g\u1ea7n, b\u1ecb \u1ea3nh h\u01b0\u1edfng b\u1edfi k\u00ednh<\/td>\n<\/tr>\n
        Nh\u1eadn di\u1ec7n gi\u1ecdng n\u00f3i<\/td>\nC\u00f3 th\u1ec3 s\u1eed d\u1ee5ng t\u1eeb xa, kh\u00f4ng ti\u1ebfp x\u00fac<\/td>\nC\u00f3 th\u1ec3 b\u1ecb \u1ea3nh h\u01b0\u1edfng b\u1edfi ti\u1ebfng \u1ed3n, b\u1ec7nh t\u1eadt<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

        Quan \u0111i\u1ec3m v\u00e0 c\u00f4ng ngh\u1ec7 t\u01b0\u01a1ng lai<\/h2>\n

        T\u01b0\u01a1ng lai c\u1ee7a nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t bao g\u1ed3m nh\u1eefng ti\u1ebfn b\u1ed9 trong k\u1ef9 thu\u1eadt h\u1ecdc s\u00e2u, \u0111i\u1ec7n to\u00e1n bi\u00ean v\u00e0 c\u00e1c thu\u1eadt to\u00e1n \u0111\u1ea1o \u0111\u1ee9c \u0111\u1ec3 gi\u1ea3m thi\u1ec3u s\u1ef1 thi\u00ean v\u1ecb. Nh\u1eefng ph\u00e1t tri\u1ec3n nh\u01b0 nh\u1eadn d\u1ea1ng c\u1ea3m x\u00fac v\u00e0 ph\u00e2n t\u00edch d\u1ef1 \u0111o\u00e1n c\u0169ng mang \u0111\u1ebfn nh\u1eefng kh\u1ea3 n\u0103ng h\u1ea5p d\u1eabn.<\/p>\n

        M\u00e1y ch\u1ee7 proxy v\u00e0 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t<\/h2>\n

        M\u00e1y ch\u1ee7 proxy c\u00f3 th\u1ec3 \u0111\u00f3ng m\u1ed9t vai tr\u00f2 trong h\u1ec7 th\u1ed1ng nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t b\u1eb1ng c\u00e1ch cung c\u1ea5p t\u00ednh n\u0103ng \u1ea9n danh cho ng\u01b0\u1eddi d\u00f9ng, b\u1ea3o v\u1ec7 h\u1ecd kh\u1ecfi c\u00e1c m\u1ed1i \u0111e d\u1ecda v\u00e0 t\u1ea5n c\u00f4ng ti\u1ec1m \u1ea9n. Ngo\u00e0i ra, ch\u00fang c\u00f3 th\u1ec3 tr\u1ee3 gi\u00fap th\u1ef1c hi\u1ec7n c\u00e1c t\u00e1c v\u1ee5 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t \u0111\u01b0\u1ee3c ph\u00e2n ph\u1ed1i b\u1eb1ng c\u00e1ch chuy\u1ec3n h\u01b0\u1edbng l\u01b0u l\u01b0\u1ee3ng truy c\u1eadp \u0111\u1ebfn c\u00e1c m\u00e1y ch\u1ee7 kh\u00e1c nhau, gi\u1ea3m t\u1eafc ngh\u1ebdn m\u1ea1ng v\u00e0 c\u1ea3i thi\u1ec7n hi\u1ec7u su\u1ea5t t\u1ed5ng th\u1ec3 c\u1ee7a h\u1ec7 th\u1ed1ng.<\/p>\n

        Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n
          \n
        1. Vi\u1ec7n Ti\u00eau chu\u1ea9n v\u00e0 C\u00f4ng ngh\u1ec7 Qu\u1ed1c gia (NIST) - Nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t<\/a><\/li>\n
        2. ACLU v\u1ec1 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t<\/a><\/li>\n
        3. IEEE Xplore \u2013 C\u00f4ng ngh\u1ec7 nh\u1eadn di\u1ec7n khu\u00f4n m\u1eb7t<\/a><\/li>\n
        4. C\u00f4ng ngh\u1ec7 nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t: S\u1ef1 c\u1ea7n thi\u1ebft c\u1ee7a quy \u0111\u1ecbnh c\u00f4ng v\u00e0 tr\u00e1ch nhi\u1ec7m c\u1ee7a doanh nghi\u1ec7p<\/a><\/li>\n<\/ol>","protected":false},"featured_media":0,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-477177","wiki","type-wiki","status-publish","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Facial Recognition: A Comprehensive Look Into the Future of Identification<\/mark>","faq_items":[{"question":"What is facial recognition technology?","answer":"

          Facial recognition is a biometric technology used to identify or verify a person's identity using their face. It captures, analyzes, and compares patterns based on the person's facial details.<\/p>"},{"question":"What was the first facial recognition system?","answer":"

          The idea of facial recognition dates back to the 1960s when Woodrow Wilson Bledsoe developed a system capable of classifying photos of faces manually using a RAND tablet.<\/p>"},{"question":"How does facial recognition technology work?","answer":"

          Facial recognition technology works by detecting, aligning, normalizing, encoding, and then matching a facial image with the known faces in a database. It uses artificial intelligence and deep learning algorithms to train on a vast number of faces and recognize patterns.<\/p>"},{"question":"What are the key features of facial recognition?","answer":"

          Key features of facial recognition technology include its non-contact process, high scalability, ability to be integrated with existing surveillance systems, and real-time identification capability.<\/p>"},{"question":"What are the different types of facial recognition?","answer":"

          There are various types of facial recognition technology such as Traditional or Geometric Facial Recognition, 3D Facial Recognition, Thermal Facial Recognition, and Skin Texture Analysis.<\/p>"},{"question":"What are the uses and challenges of facial recognition technology?","answer":"

          Facial recognition technology is used in many fields like law enforcement, surveillance, access control, marketing, and social media. However, it poses challenges such as privacy concerns, potential bias, and accuracy issues.<\/p>"},{"question":"How does facial recognition compare with other biometric technologies?","answer":"

          Facial recognition, like other biometric technologies such as fingerprint recognition, iris recognition, and voice recognition, serves the purpose of identifying individuals. However, their characteristics and performance can vary significantly.<\/p>"},{"question":"What are the future perspectives of facial recognition?","answer":"

          The future of facial recognition includes advancements in deep learning techniques, edge computing, and ethical algorithms to reduce bias. Developments like emotion recognition and predictive analytics also offer intriguing possibilities.<\/p>"},{"question":"How can proxy servers be used with facial recognition?","answer":"

          Proxy servers can provide anonymization to users of facial recognition systems, protecting them from potential threats and attacks. They can also assist in distributed facial recognition tasks, reducing network congestion and improving overall system performance.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/477177","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/477177\/revisions"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=477177"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}