Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data
➤ Gửi thông báo lỗi ⚠️ Báo cáo tài liệu vi phạmNội dung chi tiết: Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data
Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data
VIETNAM NATIONAL UNIVERSITY. HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYTA VIET CUÔNGAPPLY INCREMENTAL LEARNING FOR DAILY ACTIVITY RECOGNITION USING Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data G LOW LEVEL SENSOR DATAMASTER THESIS OF INFORMATION TECHNOLOGYHa Noi, 2012VIETNAM NATIONAL UNIVERSITY. HANOI UNIVERSITY OF ENGINEERING AND TECHNOLOGYTA \ IET CUONGAPPLY INCREMENTAL LEARNING FOR DAILY ACTIVITY RECOGNITION USING LOW LEVEL SENSOR DATAMajor: Computer Science Code: 60.48.01MASTER THESIS Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data OF INFORMATION TECHNOLOGYSupervised by Assoc. Prof. Bui The DuyHa Noi. 2012ịA thesis submitted in fulfillment of the requirements for the degree of MaLuận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data
ster of Computer ScienceSupervisor:ORIGINALITY STATEMENT‘I hereby declare that this submission is my own work and to the! best of my knowledge it contVIETNAM NATIONAL UNIVERSITY. HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYTA VIET CUÔNGAPPLY INCREMENTAL LEARNING FOR DAILY ACTIVITY RECOGNITION USING Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data any other degree or diploma at. University of Engineering and Technology or any other educational institution, except when' due acknowledgement Is made in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to thí' extent that assistance from Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data others in the project’s design and conception or in style, presentation and linguistic expression is acknowledged.’Signed............................Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data
....iiAbstractDaily activity recognition is an important task of many applications. especially in an environment like smart home. The system needs to VIETNAM NATIONAL UNIVERSITY. HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYTA VIET CUÔNGAPPLY INCREMENTAL LEARNING FOR DAILY ACTIVITY RECOGNITION USING Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data has been proposed to classify activities. However, most, of them only work well in off-line manner when training data is known in advance. It is known that people's living habits change over time, therefore a learning technique that should learn new knowledge when there is new data in great demand.I Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data n this thesis, we improve an existing incremental learning model to solve this problem. The model, which is traditionally used in unsupervised learninLuận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data
g, is extended for classification problems. Incremental learning strategy by evaluating the error classificat ion is applied when deciding whet her a VIETNAM NATIONAL UNIVERSITY. HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYTA VIET CUÔNGAPPLY INCREMENTAL LEARNING FOR DAILY ACTIVITY RECOGNITION USING Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data ors. To avoid constant allocation of new nodes ill the overlapping region, an adaptive insertion constraint is added. Finally, an experiment is carried to assess its performance. The results show that the proposed method is better than the previous one. The proposed method can be integrated into a s Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data malt system, which then pro-actively adapts itself to the changes of human daily activity pattern.AcknowledgementsI would like to express my respect aLuận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data
nd appreciation to my supervisor, Associate Professor Bui The Duy. lie is the person to guide me the approach of the thesis’s problem. He has given meVIETNAM NATIONAL UNIVERSITY. HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYTA VIET CUÔNGAPPLY INCREMENTAL LEARNING FOR DAILY ACTIVITY RECOGNITION USING Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data Dr. Vu L hi Hong Nhan for her valuable discussions about the det ails aspects of my thesis, and also for her recommendations for providing a background of my research. I also want to thank for my colleagues and friends in Human Machine Laboratory for their friendly and willingness to help me during Luận văn thạc sĩ VNU UET apply incremental learning for daily activity recognition using low lever sensor data the time I studied.iiVIETNAM NATIONAL UNIVERSITY. HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYTA VIET CUÔNGAPPLY INCREMENTAL LEARNING FOR DAILY ACTIVITY RECOGNITION USINGVIETNAM NATIONAL UNIVERSITY. HANOIUNIVERSITY OF ENGINEERING AND TECHNOLOGYTA VIET CUÔNGAPPLY INCREMENTAL LEARNING FOR DAILY ACTIVITY RECOGNITION USINGGọi ngay
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