

吳朝暉
從事知識工程與智能系統的研究。
個性化簽名
- 姓名:吳朝暉
- 目前身份:
- 擔任導師情況:
- 學位:
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學術頭銜:
博士生導師
- 職稱:-
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學科領域:
計算機應用
- 研究興趣:從事知識工程與智能系統的研究。
從1988年研究生階段開始從事知識工程與智能系統的研究,研制了當時國內第一個基于C語言的知識開發工具ZIPE。后去德國國家人工智能研究中心DFKI,從事分布式人工智能DAI領域的研究,申請人的“耦合知識表達框架”博士論文,就是探索網絡分布系統中信息共享與交換的知識表達問題。
1993年留學回國后,正值國內外人工智能研究處于平穩發展、應用滲透的階段;以互聯網為核心的網絡技術正在迅速興起,海量數據的管理與挖掘急需方法與技術,以語音人臉識別、自然語言理解為代表的AI難題仍然是學術界不斷努力解決的目標。申請人自從90年代中后期以來,在分布式AI與計算智能的工作基礎上,主要圍繞智能系統(Intelligent Systems)領域開展研究;即以語義模型與AI體系結構為研究主線,研究分布網絡智能系統,以中醫藥、交通服務、分布協同設計等網絡智能應用為背景,重點研究語義網格的模型、平臺,以及中醫藥網絡的 智能應用;以機器學習與實時嵌入平臺為研究主線,研究高性能生物認證模型與方法,以解決在普適計算環境下人機交互中自然身份特征認證為背景,圍繞說話人識別和3D人臉識別的科學問題,重點研究高性能的生物認證模型、算法,以及嵌入式說話人的實時識別系統。
申請者從80年代后期起就開始以第一參加人員身份參與導師承擔的國家自然科學基金項目研究(項目號:69175013),學成回國后承擔的第一個國家級項目也來自國家自然科學基金委支持(項目號:69503008)。近五年來,申請者承擔過或正在承擔國家973計劃、國家自然科學基金、863計劃、教育部“新世紀人才”計劃、省杰出青年基金、國家科技部基礎工作計劃、國家發改委產業化前關鍵技術計劃、教育部博士點基金等20多項國家以及國際合作項目。申請者十分注意結合重大應用需求,開展基礎應用研究;至今為此,獲國家級科技進步二等獎1項,省部級科技進步二等以上獎3項(見附件5)。申請待批準國家發明專利6項,已獲國家發明專利2項。已獲軟件著作權16項。
近五年來,申請者在IEEE IS、HPCA、IEE、AIM、JST、FGCS等國際期刊,以及IEEE ICIP、IJCNN、ICASSP、WACV、FGR 、TAI、以及AVBPA等國際重要會議上發表100余篇論文;其中SCI收錄41篇,EI收錄53篇(其中,Ei PageOne 5篇),專著1本,即將出版專著1本(書名為“說話人識別模型與方法”)。
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成果閱讀
1021
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成果數
10
【期刊論文】支持e-Science的網格體系結構及原型研究?
吳朝暉, 黃理燦?, 潘云鶴
軟件學報,2005,16(4):578~586,-0001,():
-1年11月30日
This paper presents an e-Science Grid architecture called Virtual and Dynamic Hierarchical Architecture (VDHA). VDHA is a decentralized architecture with some P2P properties. It also has scalable, autonomous, exact, and full service discovery properties. We have implemented a demonstration VDHA_based Grid prototype VDHAGrid, which has scalable Grid information service. VDHA_Grid is the core software for the project of the Chinese University e-Science Grid. In this paper, advantages and several protocols of the VDHA are also discussed.
VDHA, grid, e-Science, protocol, VDHA_, Grid
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【期刊論文】Text Mining for Finding Functional Community of Related Genes Using TCM Knowledge
吳朝暉, Zhaohui Wu, Xuezhong Zhou, Baoyan Liu, and Junli Chen
J.-F. Boulicaut et al. (Eds.): PKDD 2004, LNAI 3202, pp. 459-470, 2004.,-0001,():
-1年11月30日
We present a novel text mining approach to uncover the functional gene relationships, maybe, temporal and spatial functional modular interaction networks, from MEDLINE in large scale. Other than the regular approaches, which only consider the reductionistic molecular biological knowledge in MEDLINE, we use TCM knowledge(e.g. Symptom Complex) and the 50,000 TCM bibliographic records to automatically congregate the related genes. A simple but efficient bootstrapping technique is used to extract the clinical disease names from TCM literature, and term co-occurrence is used to identify the disease-gene relationships in MEDLINE abstracts and titles. The underlying hypothesis is that the relevant genes of the same Symptom Complex will have some biological interactions. It is also a probing research to study the connection of TCM with modern biomedical and post-genomics studies by text mining. The preliminary results show that Symptom Complex gives a novel top-down view of functional genomics research, and it is a promising research field while connecting TCM with modern life science using text mining. Keywords: Text Ming, Traditional Chinese Medicine, Symptom Complex, Gene Functional Relationships
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【期刊論文】Speaker recognition using continuous density support vector machines
吳朝暉, Xin Dong, and Wu Zhaohui
ELECTRONICS LETTERS 16th August 2001 Vol. 37 No. 17,-0001,():
-1年11月30日
A new classification system for text-independent speaker recognition is presented. This system conibines thc output probabilities of gcnerativc Gaussian mixture models and discriminative classifier support vector machines. The new method is tested on the YOHO database and achieves superior performance.
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【期刊論文】Ontology Development for Unified Traditional Chinese Medical Language System
吳朝暉, Xuezhong Zhou, ?, Zhaohui Wu, Aining Yin, Lancheng Wu, Weiyu Fan, Ruen Zhang
,-0001,():
-1年11月30日
Traditional Chinese Medicine (TCM) as a complete knowledge system researches into human health conditions via a different approach compared to orthodox medicine. We are developing a Unified Traditional Chinese Medical Language System (UTCMLS) through an ontology approach that will support TCM language knowledge storage, concept-based information retrieval and information integration. UTCMLS is a huge knowledge project, which is a broad collaboration of 16 distributed groups, most of them with no prior experience of formal ontology development. Therefore, the cooperative and comprehensive ontology engineering is crucial. We use Prot
Traditional Chinese Medicine,, Ontology Development,, Medical Language System
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吳朝暉, 封毅
,-0001,():
-1年11月30日
KDD是從海量數據中獲取有效、新穎、有潛在應用價值和最終可理解的模式的信息技術。中醫藥學是中華民族的文化瑰寶,幾千年來積累了海量的數據,采用KDD技術從這數據的汪洋大海中發現有意義的知識,對于中醫藥的信息化來講既是必要的,也是可行的。近幾年來,我們在中醫藥海量數據數字化的基礎上進行了中醫藥領域的KDD探索,取得了一系列成果。實踐表明,利用KDD技術進行中醫藥知識發現是有效的、有前景的,并能推動中醫藥的信息化進程。
KDD中醫藥, 數據挖掘, 知識發現
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【期刊論文】3D FACE RECOGNITION FROM RANGE DATA
吳朝暉, GANG PAN, and ZHAOHUI WU
May 27, 2004 3:30 WSPC/INSTRUCTION FILE,-0001,():
-1年11月30日
3D facial data is potential to overcome the problems of illumination and pose variation in face recognition. In this paper, we investigate face recognition from range data by facial profiles and surface. An efficient symmetry plane detection method for facial range data is presented to help extract facial profile. A global profile matching method is exploited to align and compare two profiles, without detection of fiducial points that is often unreliable. The central profile and two kinds of horizontal profiles-nose-crossing profile and forehead-crossing profile, are employed in recognition. For each individual, a statistical model is built to represent the distinct discriminative capability of the different regions on the facial surface, then is incorporated into a weighted distance function to measure similarity of surfaces. The comparable experimental results are achieved on a facial range data database with 120 individuals.
3D Face recognition, surface matching, facial profile, symmetry plane detection.,
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【期刊論文】RDF-Based Schema Mediation for Database Grid
吳朝暉, Huajun Chen, Zhaohui Wu, Guozhou Zheng, Yuxing Mao
,-0001,():
-1年11月30日
In presence of Grid where a huge amount of databases can be involved in sharing cycle, database tools and middlewares should be well suited for schema mediation and query processing in a semantically meaningful way. Dart is an implemented prototype system whose goal is to provide a semantic solution for database resource sharing capable of deployment in grid settings. This paper particularly concerns the problems of schema mediation in DartGrid?. Our approach mainly involves the following notions: a) we use RDF/OWL to define the mediated ontologies for integration, b) we devise a set of rules for automatically converting the relational schema to RDF/OWL description called source data semantic ,c)we define the source data semantic (source schema) as the view of shared ontologies (mediated schema),d) query is formulated and posed on the shared ontologies. A set of grid services are developed for the implementation of above functionalities.
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【期刊論文】Dynamic Bayesian network approach to speaker identification
吳朝暉, Lifeng Sang, Yingchun Yang, Zhaohui Wu, and Wanfeng Zhang
ELECTRONICS LE'TTERS.. 6th February 2003 Vol. 39 No.3,-0001,():
-1年11月30日
Dynamic Bayesian networks (DBNs) are knowledge representation schcmes that can chamtense probabilistic relationships over timese& dam and prrfumi probabilistic inference. A new approach IO speaker identification using DBNs is presented. Superior reSultS are achieved in experiments over a subset orYOHO corpus.
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【期刊論文】DartGrid II:A Semantic Grid Platform for ITS
吳朝暉, Zhaohui Wu, Shuming Tang, Shuiguang Deng, Jian Wu, Huajun Chen, and Haijun Gao
IEEE Intelligent System vol.20, No.3, June, 2005,-0001,():
-1年11月30日
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【期刊論文】AUTOMATIC 3D FACE VERIFICATION FROM RANGE DATA
吳朝暉, Gang Pan, Zhaohui Wu, Yunhe Pan
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-1年11月30日
In this paper, we presented a novel approach for automatic 3D face verification from range data. The method consists of range data registration and comparison. There are two steps in registration procedure: the coarse step conducting the normalization by exploiting a priori knowledge of the human face and facial features, and the fine step aligning the input data with the model stored in the database by the partial directed Hausdorff distance. To speed up the registration, a simplified version of the model is generated for each model in the model database. During the face comparison, the partial Hausdorff distance is employed as the similarity metric. The experiments are carried out on a database with 30 individuals, and the best EER of 3.24% is achieved.
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