Social graph analysis for verification and fill out users’ information

Social graph analysis for verification and fill out users’ information

Dữ liệu mạng xã hội bên cạnh dữ liệu hồ sơ người dùng còn có thêm thông tin về quan hệ của họ với những người khác. Hai nhóm thông tin này có mối quan hệ chặt chẽ với nhau. Do vậy, nếu được phân tích đúng chúng có thể được dùng để bổ sung hoặc kiểm tra chéo lẫn nhau. Một trong những khó khăn lớn nhất của việc ứng dụng dữ liệu mạng xã hội trong kinh doanh là dữ liệu hồ sơ người dùng rất thưa và kém chính xác. Bằng việc sử dụng một số thuật toán embedding thông tin về mối quan hệ xã hội và các thuật toán dự đoán, phân lớp khác trên đó, ta có thể kiểm chứng hoặc/và bổ sung thông tin hồ sơ của người dùng để chúng trở nên hoàn thiện và có ý nghĩa kinh doanh hơn.

Mr. Le Minh – Five9 (Vietnam)

AI in Electro-Optical/Infrared camera surveillance systems

AI in Electro-Optical/Infrared camera surveillance systems

Nowadays, Electro-Optical and Infrared (EO/IR) technology plays a critical role in many military, defense, security and industry applications; as it provides the day-night and long-range visualization capability, improves the user’s ability to automatically identify targets, performs threat assessment, raises situational awareness, as well as supports weapons engagement through automatic surveillance and fire control solutions through line-of-sight. In this talk, we will introduce several modern EO/IR camera systems that are currently being developed in Viettel R&D Institute. Furthermore, we will propose a number of artificial intelligence applications that equip our EO/IR camera surveillance systems with the ability to automatically perform detection, localization, recognition, identification and tracking of all ground/air/maritime target types in real time. Our solutions are based on some most advanced machine-learning and deep-learning models trained on large-scale data. Several techniques of online learning and multi-sensor fusion will also be proposed to provide our system with high-performance accuracies and low false alarm rates, even in bad-seeing conditions or complex backgrounds.

Dr. Dao Duc Minh – Viettel R&D (Vietnam)

Dr. Minh Dao received the B.Sc. degree in Electrical Engineering from Hanoi University of Technology, Vietnam in 2007, the double Master degree in Information and Communication Technologies from Polytechnic University of Turin, Italy, and Karlsruhe Institute of Technology, Germany in 2009, and the Ph.D.in Electrical and Computer Engineering from The Johns Hopkins University, Baltimore MD, USA, in 2015. From 2015 to 2017, he worked as a Research Scientist in the U.S. Army Research Laboratory (ARL) in Maryland, USA. In June of 2017, he joined Viettel R&D Institute, where he currently leads the Image Processing R&D team. His research interests are broadly in the areas of signal/image/video processing, statistical machine learning, computer vision and artificial intelligence.

Structured prediction for the summarisation and alignment of videos

Structured prediction for the summarisation and alignment of videos

In this talk, I present two approaches for the automated summarisation and the automated alignment of videos based on structured prediction. The first approach aims to summarise an action video by a selection of its frames while simultaneously recognising its main action. The second approach aims to find the best alignment of two given videos and can be used as a generalised distance for video classification. Both approaches are similar in spirit and leverage structured prediction and the structural SVM framework for inference and for training. Potentially, they could be coupled with deep learning layers to capture the best of both worlds.

Prof. Massimo Piccardi – University of Technology Sydney (Australia)

Massimo Piccardi (M.Eng., 1991, Ph.D. Bologna, 1995) is a professor at University of Technology Sydney (UTS) where he serves as a discipline leader for the School of Electrical and Data Engineering and as a program leader for the Global Big Data Technology Centre, a University-supported task force in communications and big data analytics. His main research areas are computer vision, multimedia, machine learning, and, more recently, natural language processing. Prof. Piccardi has published over a hundred and fifty papers to date, is a Senior Member of the IEEE and serves as an Associate Editor for journal “Computer Vision and Image Understanding.

20 years of Vietnamese Spoken Language Processing: Research & Achievements

20 years of Vietnamese Spoken Language Processing: Research & Achievements

In this talk, I will represent some of various research carried out over the last 20 years in the area of spoken language processing and discusses the major themes and advance made in the last 20 years of research at the Artificial Intelligence Laboratory (AILab), the University of Science (VNUHCM), in order to show the outlook of technology, progress and applications that have been achieved in this field.

Assoc. Prof. Vu Hai Quan – VNUHCM University of Science (Vietnam)

Vu Hai Quan received the Ph.D. degree from University of Trento (Italy) in Information and Telecommunications. He did postdoctoral training at University of Leuven (Belgium) from 2005 until 2006. He served as Vice President Vietnam National University – HoChiMinh city. His research interrest is about AI, particularly including: Acoustic Modeling, Language Modeling for LVCSR; Corpus Developments (audio & text) Audio, Music Retrieval; Speech Translation. He has published various articles on international journals and participated in many academic research projects. He won two-time Vietnamese Talent Awards for the TTS and the Automatic Speech Recognition systems.

Evolutionary computation and its roles in AI

Evolutionary computation and its roles in AI

Evolutionary computation is a nature-inspired computing paradigm. It has been a popular research area in AI in the last couple of decades. In this talk, I will cover the recent development in evolutionary algorithms, especially using directional information for guiding evolutionary search. In particular, I will introduce the concept of direction of improvement in both aspects convergence and spreading. Some newly proposed works from our research group related to this will also discussed during the talk.

Assoc. Prof. Bui Thu Lam – Le Quy Don University (Vietnam)

Dr. Lam Thu BUI received the Ph.D. degree in computer science from the University of New South Wales (UNSW), Australia, in 2007. He did postdoctoral training at UNSW from 2007 until 2009.
He has been involved with academics including teaching and research since 1998. Currently, he is an Associate Professor and Dean of IT Faculty, Le Quy Don Technical University, Hanoi, Vietnam. He is doing research in the field of evolutionary computation, specialized with evolutionary multiobjective optimization. He is the co-editor of the book Multiobjective Optimization in Computational Intelligence: Theory and Practice (IGI Global Information Science Reference Series); and the General Chair of the Ninth International Conference on Simulated Evolution and Learning – SEAL2012.
Dr. Bui is EiC of Journal of Science and Technology: Section on Information and Communication Technology (LQDTU-JICT), a member of the Editorial Board, International Journal of Computational Intelligence and Applications (IJCIA), and was the Vice-Chair of the Evolutionary Computation Technical Committee (ECTC), IEEE Computational Intelligence Society. He has been a member of the program committees of several conferences and workshops in the field of evolutionary computing, such as the IEEE Congress on Evolutionary Computation and the Genetic and Evolutionary Computation Conference.