3-D Object Recognition Using Neural Network Classification and Pyramid Feature Extraction Technique
碩士 === 國立交通大學 === 控制工程系 === 84 === We propose an approach to 3-D object recognition irrespective of its position, size, and orientation. We use a fuzzy measure technique to find an optimal threshold value and obtain the shape o...
Main Authors: | Lin, Chuan-Chung, 林傳崇 |
---|---|
Other Authors: | Sheng-Fuu Lin |
Format: | Others |
Language: | zh-TW |
Published: |
1996
|
Online Access: | http://ndltd.ncl.edu.tw/handle/12081833368431441615 |
Similar Items
-
Grouped Pyramid Convolutional Neural Networks for Human-Object Interaction Recognition
by: Kang, Ruei-Lin, et al.
Published: (2016) -
Adaptive Feature Pyramid Networks for Object Detection
by: Chengyang Wang, et al.
Published: (2021-01-01) -
Modeling multiple object scenarios for feature recognition and classification using cellular neural networks
by: Malumedzha, Tendani Calven
Published: (2009) -
Adaptively Dense Feature Pyramid Network for Object Detection
by: Haodong Pan, et al.
Published: (2019-01-01) -
Scale Adaptive Feature Pyramid Networks for 2D Object Detection
by: Lifei He, et al.
Published: (2020-01-01)