{"id":38648,"date":"2023-09-22T10:43:04","date_gmt":"2023-09-22T03:43:04","guid":{"rendered":"https:\/\/beta.gymadom.com\/nghien-cuu-khoa-hoc-cua-sinh-vien-va-hoc-vien-cao-hoc-duoc-chap-nhan-tai-hoi-nghi-so-1-the-gioi-ve-tri-tue-nhan-tao\/"},"modified":"2023-11-13T14:23:39","modified_gmt":"2023-11-13T07:23:39","slug":"nghien-cuu-khoa-hoc-cua-sinh-vien-va-hoc-vien-cao-hoc-duoc-chap-nhan-tai-hoi-nghi-so-1-the-gioi-ve-tri-tue-nhan-tao","status":"publish","type":"post","link":"https:\/\/gymadom.com\/nghien-cuu-khoa-hoc-cua-sinh-vien-va-hoc-vien-cao-hoc-duoc-chap-nhan-tai-hoi-nghi-so-1-the-gioi-ve-tri-tue-nhan-tao\/","title":{"rendered":"NGHI\u00caN C\u1ee8U KHOA H\u1eccC C\u1ee6A SINH VI\u00caN V\u00c0 H\u1eccC VI\u00caN CAO H\u1eccC \u0110\u01af\u1ee2C CH\u1ea4P NH\u1eacN T\u1ea0I H\u1ed8I NGH\u1eca S\u1ed0 1 TH\u1ebe GI\u1edaI V\u1ec0 TR\u00cd TU\u1ec6 NH\u00c2N T\u1ea0O."},"content":{"rendered":"<p style=\"text-align: justify;\"><span style=\"font-family: 'times new roman', times, serif; font-size: 14pt; color: #000000;\">Ch\u00fac m\u1eebng B\u00e0i b\u00e1o <em>\u201cLVM-Med: Learning large-scale self-supervised vision models for medical imaging via second-order graph matching\u201d<\/em> (Nh\u00f3m t\u00e1c gi\u1ea3: <a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Nguyen,+D+M+H\">Duy M. H. Nguyen<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Nguyen,+H\">Hoang Nguyen<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Diep,+N+T\">Nghiem T. Diep<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Pham,+T+N\">Tan N. Pham<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Cao,+T\">Tri Cao<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Nguyen,+B+T\">Binh T. Nguyen<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Swoboda,+P\">Paul Swoboda<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Ho,+N\">Nhat Ho<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Albarqouni,+S\">Shadi Albarqouni<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Xie,+P\">Pengtao Xie<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Sonntag,+D\">Daniel Sonntag<\/a>,\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Niepert,+M\">Mathias Niepert<\/a>) v\u1eeba \u0111\u01b0\u1ee3c ch\u1ea5p nh\u1eadn t\u1ea1i NeurIPS 2023.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-family: 'times new roman', times, serif; font-size: 14pt; color: #000000;\">C\u00e1c b\u1ea1n sinh vi\u00ean v\u00e0 h\u1ecdc vi\u00ean cao h\u1ecdc tham gia nghi\u00ean c\u1ee9u, g\u1ed3m c\u00f3:<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-family: 'times new roman', times, serif; font-size: 14pt; color: #000000;\">(1) Nguy\u1ec5n H\u1ed3 Minh Duy: C\u1ef1u sinh vi\u00ean Khoa To\u00e1n &#8211; Tin h\u1ecdc, nghi\u00ean c\u1ee9u sinh ng\u00e0nh Machine Learning t\u1ea1i Max-Planck Institute, \u0110\u1ee9c. (Co-first author)<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-family: 'times new roman', times, serif; font-size: 14pt; color: #000000;\">(2) Nguy\u1ec5n Minh Ho\u00e0ng: Sinh vi\u00ean n\u0103m 4, khoa To\u00e1n &#8211; Tin h\u1ecdc (Co-first author)<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-family: 'times new roman', times, serif; font-size: 14pt; color: #000000;\">(3) Cao Thi\u00ean Tr\u00ed, C\u1ef1u sinh vi\u00ean Ch\u01b0\u01a1ng tr\u00ecnh Ti\u00ean ti\u1ebfn ng\u00e0nh Khoa h\u1ecdc M\u00e1y t\u00ednh, Khoa C\u00f4ng ngh\u1ec7 Th\u00f4ng tin<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-family: 'times new roman', times, serif; font-size: 14pt; color: #000000;\">(4) Ph\u1ea1m Ng\u1ecdc T\u00e2n: H\u1ecdc vi\u00ean cao h\u1ecdc ng\u00e0nh Tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-family: 'times new roman', times, serif; font-size: 14pt; color: #000000;\">(5) Di\u1ec7p T\u01b0\u1eddng Nghi\u00eam, sinh vi\u00ean n\u0103m 2 &#8211; Ch\u01b0\u01a1ng tr\u00ecnh Ti\u00ean ti\u1ebfn ng\u00e0nh Khoa h\u1ecdc M\u00e1y t\u00ednh, Khoa C\u00f4ng ngh\u1ec7 Th\u00f4ng tin<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span style=\"font-size: 14pt;\"><span style=\"font-family: 'times new roman', times, serif; color: #000000;\">B\u00e0i b\u00e1o c\u00e1o t\u1eadp trung x\u00e2y d\u1ef1ng c\u00e1c pre-trained models cho \u1ea3nh y khoa. \u0110\u1ec3 l\u00e0m \u0111\u01b0\u1ee3c nh\u01b0 v\u1eady th\u01b0\u1eddng r\u1ea5t kh\u00f3 v\u00ec v\u1ea5n \u0111\u1ec1 domain-shifts trong \u1ea3nh y khoa (ch\u1eb3ng h\u1ea1n, \u1ea3nh CT, MRI, X-ray th\u00ec c\u00f3 nhi\u1ec1u \u0111\u1eb7c t\u00ednh kh\u00e1c nhau). B\u00e0i b\u00e1o \u0111\u00e3 gi\u1ea3i quy\u1ebft v\u1ea5n \u0111\u1ec1 n\u00e0y b\u1eb1ng vi\u1ec7c \u0111\u1ec1 xu\u1ea5t LVM-Med, n\u00f4m na l\u00e0 m\u1ed9t thu\u1eadt to\u00e1n contrastive learning d\u1ef1 v\u00e0o high-order graph matching. Trong c\u00e1c b\u00e0i to\u00e1n y khoa kh\u00f3 nh\u01b0 ph\u00e2n lo\u1ea1i kh\u1ed1i u trong n\u00e3o (Brain Tumor Classification) hay ph\u00e2n lo\u1ea1i b\u1ec7nh v\u00f5ng m\u1ea1c ti\u1ec3u \u0111\u01b0\u1eddng (Diabetic Retinopathy Grading), LVM-Med t\u1ed1t h\u01a1n r\u1ea5t nhi\u1ec1u so v\u1edbi c\u00e1c ph\u01b0\u01a1ng ph\u00e1p hi\u1ec7n t\u1ea1i (g\u1ea7n 6-7% v\u1ec1 m\u1eb7t accuracy).<\/span><\/span><\/h2>\n<ul style=\"list-style-type: circle;\">\n<li style=\"text-align: justify;\"><span style=\"font-family: 'times new roman', times, serif; font-size: 14pt; color: #000000;\">Link b\u00e0i b\u00e1o:\u00a0<a style=\"color: #000000;\" href=\"https:\/\/arxiv.org\/abs\/2306.11925\" data-saferedirecturl=\"https:\/\/www.google.com\/url?q=https:\/\/arxiv.org\/abs\/2306.11925&amp;source=gmail&amp;ust=1695438838016000&amp;usg=AOvVaw2bC6T3gCzGk5U1tY92y0hp\">https:\/\/arxiv.org\/abs\/2306.11925<\/a>\u00a0<\/span><\/li>\n<\/ul>\n<p><span style=\"font-family: 'times new roman', times, serif; font-size: 14pt; color: #000000;\">\u00a0<\/span><\/p>\n<p>\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Ch\u00fac m\u1eebng B\u00e0i b\u00e1o \u201cLVM-Med: Learning large-scale self-supervised vision models for medical imaging via second-order graph matching\u201d (Nh\u00f3m t\u00e1c gi\u1ea3: Duy M. H. Nguyen,\u00a0Hoang Nguyen,\u00a0Nghiem T. Diep,\u00a0Tan N. Pham,\u00a0Tri Cao,\u00a0Binh&#8230;<\/p>\n","protected":false},"author":3,"featured_media":32968,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[260],"tags":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/posts\/38648"}],"collection":[{"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/comments?post=38648"}],"version-history":[{"count":1,"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/posts\/38648\/revisions"}],"predecessor-version":[{"id":38763,"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/posts\/38648\/revisions\/38763"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/media\/32968"}],"wp:attachment":[{"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/media?parent=38648"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/categories?post=38648"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/gymadom.com\/wp-json\/wp\/v2\/tags?post=38648"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}