{"id":13657,"date":"2022-10-07T15:44:41","date_gmt":"2022-10-07T07:44:41","guid":{"rendered":"https:\/\/mis.npust.edu.tw\/en\/?page_id=13657"},"modified":"2023-09-07T10:56:02","modified_gmt":"2023-09-07T02:56:02","slug":"firm-files","status":"publish","type":"page","link":"https:\/\/mis.npust.edu.tw\/en\/firm-files\/","title":{"rendered":"\u6821\u5167\u5916\u7af6\u8cfd\u5f97\u734e"},"content":{"rendered":"\t\t
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t2022\u5e74<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t
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\u6d3b\u52d5\u540d\u7a31<\/td>\n\u4e3b\u8fa6\u55ae\u4f4d<\/td>\n\u4f5c\u54c1\u540d\u7a31<\/td>\n\u7372\u734e\u540d\u6b21<\/td>\n\u6307\u5c0e\u8001\u5e2b<\/td>\n\u53c3\u8207\u5b78\u751f<\/td>\n<\/tr>\n
2022\u5927\u5c08\u6821\u9662\u8cc7\u8a0a\u61c9\u7528\u670d\u52d9\u5275\u65b0\u7af6\u8cfd<\/td>\n<\/td>\n\u5c45\u5bb6\u8178\u9053\u75be\u75c5\u5065\u6aa2\u7cfb\u7d71\u958b\u767c<\/td>\nAIOT\u5275\u65b0\u61c9\u7528\u7d44 \u7b2c\u4e00\u540d\n\n\u8cc7\u8a0a\u61c9\u7528\u7d44 \u7b2c\u4e09\u540d<\/td>\n\u5433\u5ead\u80b2\u6559\u6388\n\n\u9ec3\u4e8e\u98db\u6559\u6388<\/td>\n\u8b1d\u5947\u5bb9 \u738b\u91c7\u7b51 \u5433\u5ba5\u4fde \u8cf4\u6ff0\u51f1\n\u59dc\u9594\u5091 \u6881\u744b\u5c55 \u738b\u88d5\u6210<\/td>\n<\/tr>\n
2022\u5927\u5c08\u6821\u9662\u8cc7\u8a0a\u61c9\u7528\u670d\u52d9\u5275\u65b0\u7af6\u8cfd<\/td>\n<\/td>\n\u5177\u6578\u4f4d\u97cc\u6027\u6a5f\u69cb\u8a2d\u8a08\u4e4b\u5fae\u578b\u9b5a\u83dc\u751f\u614b\u7cfb\u7d71\u5be6\u4f5c<\/td>\n\u8cc7\u8a0a\u61c9\u7528\u7d44 \u7b2c\u4e09\u540d<\/td>\n\u9f94\u65ed\u967d\u7279\u8058\u6559\u6388<\/td>\n\u9b4f\u6e50\u8ed2 \u6797\u627f\u5b89 \u9673\u54c1\u5fd7<\/td>\n<\/tr>\n
2022\u5927\u5c08\u6821\u9662\u8cc7\u8a0a\u61c9\u7528\u670d\u52d9\u5275\u65b0\u7af6\u8cfd<\/td>\n<\/td>\n\u57fa\u65bc\u4eba\u5de5\u667a\u6167\u5f71\u50cf\u8fa8\u8b58\u6280\u8853\u76e3\u63a7\u7570\u5e38\u9d5d\u96bb\u78ba\u4fdd\u9d5d\u7fa4\u5065\u5eb7\u72c0\u6cc1<\/td>\n\u7522\u5b78\u5408\u4f5c\u7d44 \u7b2c\u4e09\u540d<\/td>\n\u5433\u5ead\u80b2\u6559\u6388<\/td>\n\u8521\u627f\u6069 \u5433\u660e\u8ed2 \u5433\u96f2\u8056\n\u9673\u9756\u7444 \u5289\u5ff5\u7d14 \u912d\u90c1\u6f54<\/td>\n<\/tr>\n
2022\u667a\u6167\u611f\u6e2c\u806f\u7db2\u5275\u65b0\u61c9\u7528\u7af6\u8cfd<\/td>\n<\/td>\n\u5229\u7528AIOT\u8207\u6c23\u5473\u611f\u77e5\u6280\u8853\u6c7a\u7b56\u6c34\u679c\u6700\u4f73\u8cde-\u4ee5\u9999\u8549\u70ba\u4f8b<\/td>\n\u6700\u4f73\u5be6\u4f5c\u734e<\/td>\n\u5433\u5ead\u80b2\u6559\u6388<\/td>\n\u5433\u660e\u8ed2 \u8521\u627f\u6069 \u5433\u96f2\u8056\n\u9ec3\u5b9c\u5ead \u5468\u6977\u5d34<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t2021\u5e74<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t
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\u6d3b\u52d5\u540d\u7a31<\/td>\n\u4e3b\u8fa6\u55ae\u4f4d<\/td>\n\u4f5c\u54c1\u540d\u7a31<\/td>\n\u7372\u734e\u540d\u6b21<\/td>\n\u6307\u5c0e\u8001\u5e2b<\/td>\n\u53c3\u8207\u5b78\u751f<\/td>\n<\/tr>\n
2021\u5168\u570b\u5927\u5c08\u9662\u6821\u7522\u5b78\u5275\u65b0\u5be6\u4f5c\u7af6\u8cfd<\/td>\n<\/td>\n\u81ea\u52d5\u5316\u7a2e\u9d5d\u7ba1\u7406\u8207\u9d5d\u96bb\u884c\u70ba\u5206\u6790\u7cfb\u7d71-\u4f7f\u7528yolov5<\/td>\n\u6700\u4f73\u5be6\u4f5c\u734e<\/td>\n\u5433\u5ead\u80b2\u6559\u6388<\/td>\n\u8521\u627f\u6069 \u6797\u8056\u535a \u4f59\u5b5f\u502b \u694a\u923a\u7487<\/td>\n<\/tr>\n
2021\u5e74\u7b2c26\u5c46\u5927\u5c08\u6821\u9662\u8cc7\u8a0a\u61c9\u7528\u670d\u52d9\u5275\u65b0\u7af6\u8cfd<\/td>\n<\/td>\n\u916a\u8fb2\u667a\u6167\u7db2-\u4e73\u725b\u59ff\u614b\u611f\u77e5\u8207\u5065\u5eb7\u7ba1\u7406\u7cfb\u7d71<\/td>\n\u4f73\u4f5c<\/td>\n\u9f94\u65ed\u967d\u6559\u6388\n\u6f58\u5efa\u826f\u7814\u7a76\u54e1<\/td>\n\u65bd\u5b97\u4f51 \u6797\u4fca\u7fa9 \u90ed\u5bb6\u5049<\/td>\n<\/tr>\n
<\/td>\n\u5c4f\u79d1\u5927<\/td>\n<\/td>\n\u7b2c\u4e09\u7d1a\u5275\u65b0\u6559\u5b78\u512a\u826f\u6559\u5e2b\u734e<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n
<\/td>\n\u5c4f\u79d1\u5927<\/td>\n<\/td>\n\u7b2c\u4e8c\u7d1a\u5275\u65b0\u6559\u5b78\u512a\u826f\u6559\u5e2b\u734e<\/td>\n\u8521\u6b63\u767c\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t2020\u5e74<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t
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\u6d3b\u52d5\u540d\u7a31<\/td>\n\u4e3b\u8fa6\u55ae\u4f4d<\/td>\n\u4f5c\u54c1\u540d\u7a31<\/td>\n\u7372\u734e\u540d\u6b21<\/td>\n\u6307\u5c0e\u8001\u5e2b<\/td>\n\u53c3\u8207\u5b78\u751f<\/td>\n<\/tr>\n
2020\u5e74Fintech\u91d1\u878d\u670d\u52d9\u6821\u969b\u5275\u610f\u7af6\u8cfd \u65b0\u8208\u79d1\u6280\u8207\u751f\u6d3b\u91d1\u878d\u7d44<\/td>\n\u5317\u5546<\/td>\nMIS 2.0<\/td>\n\u6c7a\u8cfd\u5165\u570d<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u738b\u6631\u7fd4 \u5433\u79c9\u8b19 \u7c43\u5143\u5747 \u738b\u8ad2\u6853<\/td>\n<\/tr>\n
2020\u5e74Fintech\u91d1\u878d\u670d\u52d9\u6821\u969b\u5275\u610f\u7af6\u8cfd \u6578\u4f4d\u7406\u8ca1\u8207\u670d\u52d9\u5275\u65b0\u7d44<\/td>\n\u5317\u5546<\/td>\n\u6d6a\u8cc7\u56de\u982d<\/td>\n\u7b2c\u4e8c\u540d<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u5f35\u6377\u6069 \u6797\u6cd3\u5747 \u8521\u69ae\u5bcc<\/td>\n<\/tr>\n
2020\u5e74Fintech\u91d1\u878d\u670d\u52d9\u6821\u969b\u5275\u610f\u7af6\u8cfd<\/td>\n\u5317\u5546<\/td>\n\u5929\u5927\u5730\u5927\u5c4f\u79d1\u5927<\/td>\n\u7b2c\u4e09\u540d<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u674e\u4fca\u6bc5 \u859b\u975c\u5b9c \u5ed6\u6db4\u5a77 \u7f85\u7fa9\u68cb<\/td>\n<\/tr>\n
ACM Multimedia 2020<\/td>\n<\/td>\nSocial Media Headline Prediction Challenge<\/td>\n\u6548\u80fd\u512a\u7570\u734e<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u66fe\u6587\u6d77 \u694a\u7693\u73fd<\/td>\n<\/tr>\n
2020\u53f0\u7063\u5275\u65b0\u6280\u8853\u535a\u89bd\u6703\u767c\u660e\u7af6\u8cfd<\/td>\n<\/td>\n\u7532\u9b5a\u990a\u6b96\u7ba1\u7406\u88dd\u7f6e\u53ca\u5176\u65b9\u6cd5<\/td>\n\u9280\u724c<\/td>\n\u9673\u706f\u80fd\u6559\u6388\n\u9673\u82f1\u7537\u6559\u6388\n\u5f90\u777f\u826f\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n
IEEE International Symposium on Biomedical Imaging<\/td>\nIEEE<\/td>\n\u91ab\u5b78\u5f71\u50cf\u7814\u8a0e\u6703<\/td>\n\u4e16\u754c\u7b2c\u4e09\u540d<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u7c21\u5fd7\u5b87<\/td>\n<\/tr>\n
IEEE International Conference on Multimedia and Expo 2020(ICME2020)<\/td>\nIEEE<\/td>\n\u8cc7\u6599\u6a21\u578b\u7af6\u8cfd<\/td>\n\u4e16\u754c\u7b2c\u56db\u540d<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u99ac\u6b23\u8482 \u674e\u4fca\u6bc5<\/td>\n<\/tr>\n
European Conference on Computer Vision (ECCV)<\/td>\n<\/td>\n\u8ad6\u6587\u7af6\u8cfd<\/td>\n\u4e16\u754c\u7b2c\u4e09\u540d<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u99ac\u6b23\u8482<\/td>\n<\/tr>\n
AI\u91d1\u878d\u79d1\u6280\u5275\u65b0\u5275\u610f\u7af6\u8cfd\u65b0\u5275\u7d44<\/td>\nAI\u91d1\u878d\u79d1\u6280\u5354\u6703<\/td>\n\u7444\u5b2a\u80a1\u4efd\u7121\u9650\u516c\u53f8<\/td>\n\u7b2c\u4e09\u540d<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u674e\u6602\u73ca \u738b\u975c\u6587 \u6797\u4e91\u851a \u9673\u5f65\u829d \u9ec3\u73ee\u7444<\/td>\n<\/tr>\n
AI\u91d1\u878d\u79d1\u6280\u5275\u65b0\u5275\u610f\u7af6\u8cfd\u65b0\u5275\u7d44<\/td>\nAI\u91d1\u878d\u79d1\u6280\u5354\u6703<\/td>\n\u771f\u611bpet<\/td>\n\u4f73\u4f5c<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u9673\u8a9e\u8431 \u8521\u61b6\u79c0 \u9673\u610f\u8339<\/td>\n<\/tr>\n
AI\u91d1\u878d\u79d1\u6280\u5275\u65b0\u5275\u610f\u7af6\u8cfd\u5275\u610f\u7d44<\/td>\nAI\u91d1\u878d\u79d1\u6280\u5354\u6703<\/td>\n\u6d6a\u8cc7\u56de\u982d<\/td>\n\u4f73\u4f5c<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u5f35\u6377\u6069 \u6797\u6cd3\u5747 \u8521\u69ae\u5bcc<\/td>\n<\/tr>\n
AI\u91d1\u878d\u79d1\u6280\u5275\u65b0\u5275\u610f\u7af6\u8cfd\u5275\u610f\u7d44<\/td>\nAI\u91d1\u878d\u79d1\u6280\u5354\u6703<\/td>\n\u4f86\u6211\u5bb6\u770b\u8c93\u54aa\u5f8c\u7a7a\u7ffb<\/td>\n\u7b2c\u4e09\u540d<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u65bd\u4f51\u9716 \u694a\u5f69\u6c5d \u6797\u6631\u5ef7<\/td>\n<\/tr>\n
AI\u91d1\u878d\u79d1\u6280\u5275\u65b0\u5275\u610f\u7af6\u8cfd\u5275\u610f\u7d44<\/td>\nAI\u91d1\u878d\u79d1\u6280\u5354\u6703<\/td>\nbethebees<\/td>\n\u7b2c\u4e8c\u540d<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u859b\u975c\u5b9c \u5ed6\u6db4\u5a77 \u7f85\u7fa9\u68cb \u674e\u4fca\u6bc5<\/td>\n<\/tr>\n
AI\u91d1\u878d\u79d1\u6280\u5275\u65b0\u5275\u610f\u7af6\u8cfd\u5275\u610f\u7d44<\/td>\nAI\u91d1\u878d\u79d1\u6280\u5354\u6703<\/td>\n\u5929\u5927\u5730\u5927\u5c4f\u79d1\u5927<\/td>\n\u4f73\u4f5c<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u5433\u6e44\u6f54 \u5433\u5b9c\u73b2 \u9673\u5a49\u8339(\u8cc7\u7ba1\u7cfb) \u5433\u7fbd\u5a55 \u984f\u6708\u73ca(\u8ca1\u91d1\u5b78\u7a0b)<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t2019\u5e74<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\u6d3b\u52d5\u540d\u7a31<\/td>\n\u4e3b\u8fa6\u55ae\u4f4d<\/td>\n\u4f5c\u54c1\u540d\u7a31<\/td>\n\u7372\u734e\u540d\u6b21<\/td>\n\u6307\u5c0e\u8001\u5e2b<\/td>\n\u53c3\u8207\u5b78\u751f<\/td>\n<\/tr>\n
108\u5e74\u5ea6\u88dc\u52a9\u5927\u5c08\u6821\u9662\u734e\u52f5<\/td>\n\u79d1\u6280\u90e8<\/td>\n\u5927\u5c08\u6821\u9662\u734e\u52f5<\/td>\n<\/td>\n\u9f94\u65ed\u967d\u6559\u6388\n\u5289\u5be7\u6f22\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n
107\u5e74\u516c\u52d9\u4eba\u54e1\u666e\u901a\u8003\u8a66<\/td>\n\u8003\u8a66\u9662<\/td>\n\u8cc7\u8a0a\u8655\u7406\u985e\u79d1<\/td>\n\u53ca\u683c<\/td>\n<\/td>\n\u5433\u5764\u6d0b<\/td>\n<\/tr>\n
\u96fb\u8166\u8996\u89ba\u5716\u5b78\u53ca\u5f71\u50cf\u8655\u7406\u7814\u8a0e\u67032019<\/td>\nCVGIP 2019<\/td>\nDetecting Generated Image Based On A Coupled Network With Two-Step Pairwise Learning<\/td>\n\u4f73\u4f5c\u8ad6\u6587\u734e<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u838a\u6613\u4fee<\/td>\n<\/tr>\n
IEEE International Conference on Computer Vision (ICCV) \u7814\u8a0e\u6703<\/td>\nAdvances in Image Manipulation (AIM) Workshop\u4e2d\u8209\u8fa6\u7684Real-World Super-Resolution Challenge<\/td>\nDual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution<\/td>\n\u4e16\u754c\u7b2c\u4e94<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n
IEEE International Conference on Image Processing (ICIP)<\/td>\n<\/td>\nDetecting Generated Image based on A Coupled Network with Two-Step Pairwise Learning<\/td>\n\u6700\u4f73\u5b78\u751f\u8ad6\u6587\u734e<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u838a\u6613\u4fee<\/td>\n<\/tr>\n
Embedded Deep Learning Object Detection Model Competition<\/td>\nIEEE 21st International Workshop on Multimedia Signal Processing (MMSP)<\/td>\n<\/td>\n\u4e16\u754c\u7b2c\u4e94\u540d<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u838a\u6613\u4fee \u7c21\u5fd7\u5b87<\/td>\n<\/tr>\n
Grand Challenges on Vehicle ReIdentification<\/td>\n2019 IEEE International Conference on Visual Communications and Image Processing (VCIP)<\/td>\n<\/td>\n\u4e16\u754c\u7b2c\u4e09\u540d<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u7c21\u5fd7\u5b87 \u838a\u6613\u4fee \u6d2a\u6176\u8c6a<\/td>\n<\/tr>\n
\u7b2c24\u5c46\u8cc7\u8a0a\u61c9\u7528\u670d\u52d9\u5275\u65b0\u7af6\u8cfd<\/td>\n\u6559\u80b2\u90e8\u8cc7\u8a0a\u53ca\u79d1\u6280\u6559\u80b2\u53f8 \u4e2d\u83ef\u6c11\u570b\u8cc7\u8a0a\u7ba1\u7406\u5b78\u6703 \u7d93\u6fdf\u90e8\u5de5\u696d\u5c40<\/td>\n\u7bb1\u7db2\u990a\u6b96\u667a\u806f\u7db2\u5e73\u53f0\u7cfb\u7d71<\/td>\n\u7522\u5b78\u5408\u4f5c\u7d44\u4e09 \u4f73\u4f5c<\/td>\n\u9f94\u65ed\u967d\u6559\u6388<\/td>\n\u6797\u66c9\u742a \u7f85\u7fa9\u68cb \u5468\u6e32\u676d \u674e\u6e58\u6e1d<\/td>\n<\/tr>\n
\u7b2c24\u5c46\u8cc7\u8a0a\u61c9\u7528\u670d\u52d9\u5275\u65b0\u7af6\u8cfd<\/td>\n\u6559\u80b2\u90e8\u8cc7\u8a0a\u53ca\u79d1\u6280\u6559\u80b2\u53f8 \u4e2d\u83ef\u6c11\u570b\u8cc7\u8a0a\u7ba1\u7406\u5b78\u6703 \u7d93\u6fdf\u90e8\u5de5\u696d\u5c40<\/td>\n\u61c9\u7528\u667a\u6167\u7269\u806f\u7db2\u6280\u8853\u4e4b\u8c6c\u96bb\u98fc\u990a\u8cc7\u8a0a\u8207\u77e5\u8b58\u7ba1\u7406\u7cfb\u7d71\u5efa\u7f6e<\/td>\n\u7522\u5b78\u5408\u4f5c\u7d44\u4e8c \u4f73\u4f5c<\/td>\n\u9f94\u65ed\u967d\u6559\u6388<\/td>\n\u8521\u77e5\u8018 \u9673\u739f\u96ef \u9673\u5b8f\u745e<\/td>\n<\/tr>\n
2019FinTech\u91d1\u878d\u670d\u52d9\u2014\u6821\u969b\u5275\u610f\u7af6\u8cfd<\/td>\n\u570b\u7acb\u81fa\u5317\u5546\u696d\u5927\u5b78\u8ca1\u52d9\u91d1\u878d\u7cfb<\/td>\n\u5b78\u751f\u667a\u80fd\u79df\u5c4b\u5e73\u81fa<\/td>\n\u4f73\u4f5c<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u9ec3\u858f\u6a3a \u838a\u5b50\u8abc \u5f35\u96ef\u7b51 \u6f58\u6021\u84c9<\/td>\n<\/tr>\n
\u7b2c\u56db\u5c46\u83ef\u5357\u91d1\u63a7\u91d1\u878d\u79d1\u6280\u5275\u65b0\u7af6\u8cfd<\/td>\n\u83ef\u5357\u91d1\u63a7<\/td>\n<\/td>\n\u5165\u570d\u8907\u8cfd<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u6797\u67ef\u6069 \u5433\u58eb\u9293 \u674e\u51a0\u6a3a \u9673\u5f64<\/td>\n<\/tr>\n
\u81ea\u99d5\u8eca\u6703\u8b70 (Autonomous Driving Workshop, sponsored by Toyota)<\/td>\nIEEE International Conference on Computer Vision (ICCV) \u7814\u8a0e\u6703<\/td>\n\u81ea\u52d5\u99d5\u99db\u9810\u6e2c\u6280\u8853 (Learning to Drive Challenge)<\/td>\n\u4e16\u754c\u7b2c\u4e09<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u694a\u7693\u633a \u66fe\u6587\u6d77<\/td>\n<\/tr>\n
108\u5e74\u5ea6\u6559\u5e2b\u7814\u767c\u6210\u679c\u7af6\u8cfd<\/td>\n\u570b\u7acb\u5c4f\u6771\u79d1\u6280\u5927\u5b78<\/td>\n\u91dd\u5c0d\u6c34\u7522\u990a\u6b96\u5efa\u69cb\u7269\u806f\u7db2\u76e3\u63a7\u53ca\u667a\u6167\u751f\u7522\u5206\u6790\u8207\u61c9\u7528<\/td>\n\u7279\u512a\u4f5c\u54c1\u734e<\/td>\n\u9f94\u65ed\u967d\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n
\u7b2c\u5341\u516d\u5c46\u80b2\u79c0\u76c3\u5275\u610f\u734e<\/td>\n\u8ca1\u5718\u6cd5\u4eba\u80b2\u79c0\u6559\u80b2\u57fa\u91d1\u6703<\/td>\nSmart-detective \u667a\u6167\u5340\u57df\u806f\u9632\u76e3\u63a7\u7cfb\u7d71<\/td>\n\u4f73\u4f5c<\/td>\n\u7ae5\u66c9\u5112\u6559\u6388<\/td>\n\u6d2a\u6176\u8c6a \u5289\u4fca\u5b8f \u8521\u6770\u5ead \u8a31\u54f2\u744b \u5f35\u96ef\u96c5 \u5f35\u6587\u8aa0<\/td>\n<\/tr>\n
Social Media Prediction Challenge-1st Place<\/td>\n\u570b\u969bACM Multimedia 2019<\/td>\n<\/td>\n\u4f73\u4f5c<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u674e\u4fca\u6bc5 \u5433\u7d39\u6c11<\/td>\n<\/tr>\n
AIDEA\u958b\u653e\u8b70\u984c\u7af6\u8cfd- AOI\u5149\u5b78\u6aa2\u6e2c\u7af6\u8cfd<\/td>\n\u5de5\u7814\u9662<\/td>\n<\/td>\n\u4f73\u4f5c<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u674e\u4fca\u6bc5 \u99ac\u6b23\u8482<\/td>\n<\/tr>\n
108\u5e74\u5ea6\u88dc\u52a9\u5927\u5c08\u6821\u9662\u734e\u52f5<\/td>\n\u79d1\u6280\u90e8<\/td>\n<\/td>\n\u5927\u5c08\u6821\u9662\u734e\u52f5<\/td>\n\u9f94\u65ed\u967d\u6559\u6388\n\u5289\u5be7\u6f22\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n
Detecting Generated Image Based On A Coupled Network With Two-Step Pairwise Learning<\/td>\n\u96fb\u8166\u8996\u89ba\u5716\u5b78\u53ca\u5f71\u50cf\u8655\u7406\u7814\u8a0e\u67032019 (CVGIP 2019)<\/td>\n<\/td>\n\u4f73\u4f5c\u8ad6\u6587\u734e<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u838a\u6613\u4fee<\/td>\n<\/tr>\n
Advances in Image Manipulation (AIM) Workshop\u4e2d\u8209\u8fa6\u7684Real-World Super-Resolution Challenge<\/td>\nIEEE International Conference on Computer Vision (ICCV) \u7814\u8a0e\u6703<\/td>\nDual Reconstruction with Densely Connected Residual Network for Single Image Super-Resolution<\/td>\n\u4e16\u754c\u7b2c\u4e94<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n
<\/td>\nIEEE International Conference on Image Processing (ICIP)<\/td>\nDetecting Generated Image based on A Coupled Network with Two-Step Pairwise Learning<\/td>\n\u6700\u4f73\u5b78\u751f\u8ad6\u6587\u734e<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u838a\u6613\u4fee<\/td>\n<\/tr>\n
Embedded Deep Learning Object Detection Model Competition<\/td>\nIEEE 21st International Workshop on Multimedia Signal Processing (MMSP)<\/td>\n<\/td>\n\u4e16\u754c\u7b2c\u4e94\u540d<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u838a\u6613\u4fee \u7c21\u5fd7\u5b87<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t2018\u5e74<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t
\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\u6d3b\u52d5\u540d\u7a31<\/td>\n\u4e3b\u8fa6\u55ae\u4f4d<\/td>\n\u4f5c\u54c1\u540d\u7a31<\/td>\n\u7372\u734e\u540d\u6b21<\/td>\n\u6307\u5c0e\u8001\u5e2b<\/td>\n\u53c3\u8207\u5b78\u751f<\/td>\n<\/tr>\n
ACM MM 2018 Social Media Headline Prediction Challenge<\/td>\nACMMM\u7814\u8a0e\u6703<\/td>\nSMHP Challenge<\/td>\n\u4e16\u754c\u7b2c\u4e8c\u540d<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u4faf\u91c7\u6600 \u674e\u4fca\u6bc5 \u90ed\u745b\u8331 \u6797\u975c\u739f \u5ed6\u5ead\u7156 \u859b\u975c\u5b9c<\/td>\n<\/tr>\n
2018\u53f0\u7063\u5275\u65b0\u6280\u8853\u535a\u89bd\u6703<\/td>\n\u79d1\u6280\u90e8 \u6559\u80b2\u90e8<\/td>\n\u667a\u6167\u5ba2\u88fd\u5316\u5bf5\u7269\u98fc\u6599\u7ba1\u7406\u8207\u96fb\u5b50\u5546\u52d9\u7cfb\u7d71<\/td>\n\u53d7\u9080\u53c3\u5c55<\/td>\n\u9f94\u65ed\u967d\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n
2018\u8edf\u9ad4\u5275\u4f5c\u9054\u4eba\u6691\u671f\u6210\u9577\u71df<\/td>\n\u6559\u80b2\u90e8<\/td>\n\u652f\u63f4\u65c5\u884c\u5718\u7fa4\u9ad4\u4e92\u52d5\u53ca\u670d\u52d9\u7684APP\u958b\u767c<\/td>\n\u5357\u661f\u5275\u901f\u5668-\u7279\u5225\u734e<\/td>\n\u9f94\u65ed\u967d\u6559\u6388<\/td>\n\u9673\u5b8f\u745e \u8521\u77e5\u8018 \u59da\u66c9\u5f64<\/td>\n<\/tr>\n
2018\u8edf\u9ad4\u5275\u4f5c\u9054\u4eba\u6691\u671f\u6210\u9577\u71df<\/td>\n\u6559\u80b2\u90e8<\/td>\n\u5718\u9ad4\u8a02\u9910APP\u958b\u767c<\/td>\n\u5357\u661f\u5275\u901f\u5668-\u7279\u5225\u734e<\/td>\n\u9f94\u65ed\u967d\u6559\u6388<\/td>\n\u5468\u6e32\u676d \u7f85\u7fa9\u68cb \u6797\u66c9\u742a \u674e\u6c76\u8431 \u674e\u6e58\u6e1d<\/td>\n<\/tr>\n
Social Media Headline Prediction Challenge<\/td>\nACM Multimedia 2018<\/td>\n<\/td>\nTop Performance Award<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u4faf\u91c7\u6600 \u674e\u4fca\u6bc5 \u90ed\u745b\u8331 \u6797\u975c\u739f \u5ed6\u5ead\u7156 \u859b\u975c\u5b9c<\/td>\n<\/tr>\n
\u6c11\u751f\u96fb\u5b50\u7814\u8a0e\u6703<\/td>\nACM Multimedia 2018<\/td>\nFake face image detection using Siamese Network<\/td>\n\u512a\u826f\u8ad6\u6587\u734e<\/td>\n\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388<\/td>\n\u838a\u6613\u4fee<\/td>\n<\/tr>\n
105\u5e74\u79d1\u6280\u90e8\u5de5\u7a0b\u53f8\u8cc7\u8a0a\u5b89\u5168\u5be6\u52d9\u7814\u767c\u8a08\u756b<\/td>\n\u79d1\u6280\u90e8<\/td>\n\u96f2\u7aef\u7269\u806f\u6280\u8853\u8207\u5e73\u53f0\u8a2d\u8a08:\u4ee5\u667a\u6167\u8fb2\u696d\u70ba\u9a57\u8b49\u5834\u57df<\/td>\n\u7e3e\u512a\u5718\u968a<\/td>\n\u9f94\u65ed\u967d\u6559\u6388 \u7ae5\u66c9\u5112\u6559\u6388 \u8521\u7389\u5a1f\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n
107\u5e74\u6559\u80b2\u90e8\u8cc7\u901a\u8a0a\u8edf\u9ad4\u5275\u65b0\u4eba\u624d\u57f9\u80b2\u8a08\u756b<\/td>\n\u570b\u7acb\u5c4f\u6771\u79d1\u6280\u5927\u5b78<\/td>\n<\/td>\n\u8868\u73fe\u5091\u51fa\u66a8\u7279\u6b8a\u8ca2\u737b\u4eba\u54e1\u734e<\/td>\n\u9f94\u65ed\u967d\u6559\u6388<\/td>\n<\/td>\n<\/tr>\n
107 \u5e74\u5ea6\u53f0\u7063\u8fb2\u696d\u8cc7\u8a0a\u79d1\u6280\u767c\u5c55\u5354\u6703<\/td>\n\u53f0\u7063\u8fb2\u696d\u8cc7\u8a0a\u79d1\u6280\u767c\u5c55\u5354\u6703<\/td>\n\u7d50\u5408NLP\u8207Bi-LSTM\u4e4b\u667a\u6167\u98fc\u990a\u77e5\u8b58\u8a08\u7b97\u7cfb\u7d71\u8a2d\u8a08\u8207\u5be6\u4f5c<\/td>\n\u6700\u4f73\u78a9\u58eb\u8ad6\u6587\u734e<\/td>\n\u9f94\u65ed\u967d\u6559\u6388<\/td>\n\u5442\u570b\u8c6a<\/td>\n<\/tr>\n
107\u5e74\u516c\u52d9\u4eba\u54e1\u666e\u901a\u8003\u8a66<\/td>\n\u8003\u8a66\u9662<\/td>\n\u8cc7\u8a0a\u8655\u7406\u985e\u79d1<\/td>\n\u53ca\u683c<\/td>\n<\/td>\n\u5433\u5764\u6d0b<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t2017\u5e74<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t
\n\n\n\n\n\n\n
\u6d3b\u52d5\u540d\u7a31<\/td>\n\u4e3b\u8fa6\u55ae\u4f4d<\/td>\n\u4f5c\u54c1\u540d\u7a31<\/td>\n\u7372\u734e\u540d\u6b21<\/td>\n\u6307\u5c0e\u8001\u5e2b<\/td>\n\u53c3\u8207\u5b78\u751f<\/td>\n<\/tr>\n
106\u5b78\u5e74\u5ea6\u96f2\u7aef\u8a08\u7b97\u8207\u670d\u52d9\u5c08\u984c\u6210\u679c\u7af6\u8cfd<\/td>\n\u6559\u80b2\u90e8\u8cc7\u8a0a\u53ca\u79d1\u6280\u6559\u80b2\u53f8\u8cc7\u901a\u8a0a\u8edf\u9ad4\u5275\u65b0<\/td>\n\u7a7f\u6234\u5f0f\u500b\u4eba\u6162\u8dd1\u904b\u52d5\u53ca\u5065\u5eb7\u96f2\u7aef\u7cfb\u7d71<\/td>\n\u4f73\u4f5c<\/td>\n\u9f94\u65ed\u967d\u6559\u6388\n\u5433\u54f2\u4e00\u535a\u58eb<\/td>\n\u738b\u5fa9\u5100 \u66fe\u7fd4\u653f \u5f35\u665f\u715c \u675c\u76c8\u7192 \u738b\u5f65\u5ef7<\/td>\n<\/tr>\n
<\/td>\n\u8ca1\u5718\u6cd5\u4eba\u570b\u7acb\u5c4f\u6771\u79d1\u6280\u5927\u5b78\u6821\u53cb\u6587\u6559\u57fa\u91d1\u6703<\/td>\n<\/td>\n106\u5e74\u5ea6\u512a\u79c0\u5b78\u751f\u734e\u5b78\u91d1<\/td>\n\u9f94\u65ed\u967d\u6559\u6388\n\u5433\u54f2\u4e00\u535a\u58eb<\/td>\n\u8303\u5bb6\u90e1<\/td>\n<\/tr>\n
106\u5e74\u516c\u52d9\u4eba\u54e1\u7279\u7a2e\u8003\u8a66\u4e00\u822c\u8b66\u5bdf\u4eba\u54e1\u8003\u8a66<\/td>\n\u8003\u9078\u90e8\u7279\u7a2e\u8003\u8a66\u53f8\u7b2c\u4e09\u79d1<\/td>\n<\/td>\n\u4e00\u822c\u8b66\u5bdf\u4eba\u54e1<\/td>\n<\/td>\n\u9673\u5b87\u51e1<\/td>\n<\/tr>\n
\u91d1\u878d\u79d1\u6280\u5275\u65b0\u5168\u570b\u6821\u5712\u8ab2\u7a0b\u5408\u4f5c<\/td>\n\u91d1\u878d\u79d1\u6280\u5275\u65b0\u5275\u696d\u53ca\u4eba\u624d\u57f9\u80b2\u8a08\u756b<\/td>\n<\/td>\nFinTechBase\u4fee\u7fd2\u8b49\u660e<\/td>\n\u90b5\u654f\u83ef\u526f\u6559\u6388<\/td>\n\u5927\u4e0962\u4f4d\u5b78\u751f<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t2016\u5e74<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
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2016\u5e74\u53f0\u5317\u570b\u969b\u767c\u660e\u66a8\u6280\u8853\u4ea4\u6613\u5c55<\/td>\n\u7d93\u6fdf\u90e8\u570b\u969b\u8cbf\u6613\u5c40<\/td>\n\u57fa\u65bconeM2M\u6a19\u6e96\u4e4b\u958b\u653e\u5f0f\u7269\u806f\u7db2\u4e2d\u4ecb\u5e73\u53f0<\/td>\n\u53d7\u9080\u53c3\u5c55<\/td>\n\u9f94\u65ed\u967d\u6559\u6388<\/td>\n\u5f35\u5b87\u921e \u5f35\u7b51\u921e \u6e38\u535a\u7fd4 \u5442\u570b\u8c6a<\/td>\n<\/tr>\n
2016\u5e74\u53f0\u5317\u570b\u969b\u767c\u660e\u66a8\u6280\u8853\u4ea4\u6613\u5c55<\/td>\n\u7d93\u6fdf\u90e8\u570b\u969b\u8cbf\u6613\u5c40<\/td>\n\u667a\u6167\u8fb2\u696d\u4e4b\u690d\u683d\u75c5\u87f2\u5bb3\u5f71\u50cf\u8fa8\u8b58\u76e3\u6e2c\u53ca\u7279\u5fb5\u898f\u5247\u63a2\u52d8\u5e73\u53f0\u8a2d\u8a08\u8207\u5be6\u4f5c<\/td>\n\u53d7\u9080\u53c3\u5c55<\/td>\n\u8521\u7389\u5a1f\u6559\u6388<\/td>\n\u6c5f\u8000\u570b<\/td>\n<\/tr>\n
2016\u5e74\u53f0\u5317\u570b\u969b\u767c\u660e\u66a8\u6280\u8853\u4ea4\u6613\u5c55<\/td>\n\u7d93\u6fdf\u90e8\u570b\u969b\u8cbf\u6613\u5c40<\/td>\n\u9069\u7528\u65bc\u96f2\u7aef\u5e73\u53f0\u4e4b\u5275\u65b0\u5f71\u50cf\u58d3\u7e2eApp\u6280\u8853\u8a2d\u8a08\u8207\u958b\u767c<\/td>\n\u53d7\u9080\u53c3\u5c55<\/td>\n\u8521\u6b63\u767c\u6559\u6388<\/td>\n\u5442\u7950\u5b89 \u9673\u90c1\u5091 \u674e\u4f69\u541b \u56b4\u7acb\u51f1 \u9023\u9038\u7487<\/td>\n<\/tr>\n
2016\u5e74\u53f0\u5317\u570b\u969b\u767c\u660e\u66a8\u6280\u8853\u4ea4\u6613\u5c55<\/td>\n\u7d93\u6fdf\u90e8\u570b\u969b\u8cbf\u6613\u5c40<\/td>\nNewsRaker\u65b0\u805e\u53f2\u745e\u514b-\u96a8\u9078\u65b0\u805e\u5f71\u97f3\u983b\u9053<\/td>\n\u53d7\u9080\u53c3\u5c55<\/td>\n\u7ae5\u66c9\u5112\u6559\u6388<\/td>\n\u6797\u67cf\u7ff0<\/td>\n<\/tr>\n
2016\u7b2c21\u5c46\u5168\u570b\u5927\u5c08\u6821\u9662\u8cc7\u8a0a\u61c9\u7528\u670d\u52d9\u5275\u65b0\u7af6\u8cfd<\/td>\n\u7d93\u6fdf\u90e8\u5de5\u696d\u5c40\n\u6559\u80b2\u90e8\u8cc7\u8a0a\u53ca\u79d1\u6280\u6559\u80b2\u53f8\n\u4e2d\u83ef\u6c11\u570b\u8cc7\u8a0a\u7ba1\u7406\u5b78\u6703<\/td>\n\u667a\u6167\u6c34\u7522\u990a\u6b96\u7ba1\u7406\u8cc7\u8a0a\u7cfb\u7d71<\/td>\n\u8cc7\u8a0a\u6280\u8853\u61c9\u7528\u7d44\u4e8c \u4f73\u4f5c<\/td>\n\u9f94\u65ed\u967d\u6559\u6388<\/td>\n\u6d2a\u632f\u525b \u4f55\u5e9a\u6a3a \u8cf4\u5fd7\u7dad \u5f35\u6587\u8aa0 \u6d2a\u7adf\u8c6a \u674e\u5bb6\u8c6a<\/td>\n<\/tr>\n
2016\u7b2c21\u5c46\u5168\u570b\u5927\u5c08\u6821\u9662\u8cc7\u8a0a\u61c9\u7528\u670d\u52d9\u5275\u65b0\u7af6\u8cfd<\/td>\n\u7d93\u6fdf\u90e8\u5de5\u696d\u5c40\n\u6559\u80b2\u90e8\u8cc7\u8a0a\u53ca\u79d1\u6280\u6559\u80b2\u53f8\n\u4e2d\u83ef\u6c11\u570b\u8cc7\u8a0a\u7ba1\u7406\u5b78\u6703<\/td>\n\u89c0\u5149\u8def\u7dda\u5065\u8eab\u8eca\u64f4\u589e\u5be6\u5883\u7cfb\u7d71<\/td>\n\u8cc7\u8a0a\u6280\u8853\u61c9\u7528\u7d44\u4e00 \u7b2c\u4e09\u540d<\/td>\n\u5289\u5be7\u6f22\u6559\u6388<\/td>\n\u9673\u739f\u59a4 \u5433\u601d\u7469 \u9673\u82f1\u5b5c \u66fe\u7d0b\u7469 \u8521\u7f8e\u81ba<\/td>\n<\/tr>\n
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105\u5e74\u516c\u52d9\u4eba\u54e1\u9ad8\u7b49\u8003\u8a66\u4e09\u7d1a\u8003\u8a66<\/td>\n\u8003\u9078\u90e8\u9ad8\u666e\u8003\u8a66\u53f8\u7b2c\u4e00\u79d1<\/td>\n\u61c9\u7528\u7269\u806f\u7db2\u6280\u8853\u4e4b\u862d\u5712\u667a\u6167\u751f\u7522\u7ba1\u7406\u8207\u77e5\u8b58\u7cfb\u7d71<\/td>\n\u8cc7\u8a0a\u8655\u7406\u985e\u79d1 \u901a\u904e<\/td>\n<\/td>\n\u8b1d\u5b97\u5b8f<\/td>\n<\/tr>\n
2016\u53f0\u7063\u7db2\u8def\u667a\u80fd\u5b78\u6703<\/td>\n\u53f0\u7063\u7db2\u8def\u667a\u80fd\u5b78\u6703<\/td>\n\u61c9\u7528\u7269\u806f\u7db2\u6280\u8853\u4e4b\u862d\u5712\u667a\u6167\u751f\u7522\u7ba1\u7406\u8207\u77e5\u8b58\u7cfb\u7d71<\/td>\n\u6700\u4f73\u78a9\u58eb\u8ad6\u6587\u734e<\/td>\n\u8521\u6b63\u767c<\/td>\n\u6c5f \u8000<\/td>\n<\/tr>\n
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