skip to main content
Ngôn ngữ:
Giới hạn tìm kiếm: Giới hạn tìm kiếm: Dạng tài nguyên Hiển thị kết quả với: Hiển thị kết quả với: Chỉ mục

Scene Recognition Based on Fusion of Color and Corner Features

Chacon-Murguia, Mario I ; Guerrero-Saucedo, Cynthia P ; Sandoval-Rodriguez, Rafael; Melin, Patricia (Editor) ; Kacprzyk, Janusz (Editor) ; Pedrycz, Witold (Editor)

Studies in Computational Intelligence, Soft Computing for Recognition Based on Biometrics, pp.317-331

ISBN: 9783642151101 ; ISBN: 3642151108 ; E-ISBN: 9783642151118 ; E-ISBN: 3642151116 ; DOI: 10.1007/978-3-642-15111-8_20

Toàn văn sẵn có

Trích dẫn Trích dẫn bởi
  • Nhan đề:
    Scene Recognition Based on Fusion of Color and Corner Features
  • Tác giả: Chacon-Murguia, Mario I ; Guerrero-Saucedo, Cynthia P ; Sandoval-Rodriguez, Rafael
  • Melin, Patricia (Editor) ; Kacprzyk, Janusz (Editor) ; Pedrycz, Witold (Editor)
  • Chủ đề: Engineering ; Engineering Design ; Artificial Intelligence (Incl. Robotics) ; Biometrics ; Engineering
  • Là 1 phần của: Studies in Computational Intelligence, Soft Computing for Recognition Based on Biometrics, pp.317-331
  • Mô tả: The advance of science and technology has motivated to face new and more complex engineering applications. These new challenges must involve not only the design of adaptive and dynamic systems but also the use of correct information. Everyday, it is more evident that good multicriteria decision making systems require different types of information; therefore data fusion is becoming a paramount point in the design of multicriteria decision making systems. This chapter presents a scenery recognition system for robot navigation using a neural network hierarchical approach. The system is based on information fusion in indoor scenarios. The neural systems consist on two levels. The first level is built with one neural network and the second level with two. The system extracts relevant information with respect to color and landmarks. Color information is related mainly to localization of doors. Landmarks are related to corner detection. The hierarchical neural system, based on feedforward architectures, presents 90% of correct recognition in the first level in training, and 95% in validation. The first ANN in the second level shows 90.90% of correct recognition during training, and 87.5% in validation. The second ANN has a performance of 93.75% and 91.66% during training and validation, respectively. The total performance of the systems was 86.6% during training, and 90% in validation.
  • Nơi xuất bản: Berlin, Heidelberg: Springer Berlin Heidelberg
  • Năm xuất bản: 2010
  • Ngôn ngữ: English
  • Số nhận dạng: ISBN: 9783642151101 ; ISBN: 3642151108 ; E-ISBN: 9783642151118 ; E-ISBN: 3642151116 ; DOI: 10.1007/978-3-642-15111-8_20

Đang tìm Cơ sở dữ liệu bên ngoài...