TAILIEUCHUNG - Báo cáo hóa học: "Object Recognition System-on-Chip Using the Support Vector Machines"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Object Recognition System-on-Chip Using the Support Vector Machines | EURASIP Journal on Applied Signal Processing 2005 7 993-1004 2005 Hindawi Publishing Corporation Object Recognition System-on-Chip Using the Support Vector Machines Roberto Reyna-Rojas Laboratory for Analysis and Architecture of Systems LAAS CNRS 7 avenue du Colonel Roche 31077 Toulouse Cedex 4 France Email Dominique Houzet The Rennes Institute of Electronics and Telecommunications IETR UMR CNRS 6164 INSA 20 avenue des Buttes de Coesmes 35053 Rennes Cedex France Email houzet@ Daniela Dragomirescu Laboratory for Analysis and Architecture of Systems LAAS CNRS 7 avenue du Colonel Roche 31077 Toulouse Cedex 4 France Email daniela@ Florent Carlier The Rennes Institute of Electronics and Telecommunications IETR UMR CNRS 6164 INSA 20 avenue des Buttes de Coesmes 35053 Rennes Cedex France Email Salim Ouadjaout The Rennes Institute of Electronics and Telecommunications IETR UMR CNRS 6164 INSA 20 avenue des Buttes de Coesmes 35053 Rennes Cedex France Email Received 16 September 2003 Revised 6 June 2004 The first aim of this work is to propose the design of a system-on-chip SoC platform dedicated to digital image and signal processing which is tuned to implement efficiently multiply-and-accumulate MAC vector matrix operations. The second aim of this work is to implement a recent promising neural network method namely the support vector machine SVM used for real-time object recognition in order to build a vision machine. With such a reconfigurable and programmable SoC platform it is possible to implement any SVM function dedicated to any object recognition problem. The final aim is to obtain an automatic reconfiguration of the SoC platform based on the results of the learning phase on an objects database which makes it possible to recognize practically any object without manual programming. Recognition can be of any kind that is from image to signal data. Such a system is

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