| 期刊全稱(chēng) | Automatic Generation of Morphological Set Recognition Algorithms | | 影響因子2023 | Robert C. Vogt | | 視頻video | http://file.papertrans.cn/167/166424/166424.mp4 | | 學(xué)科分類(lèi) | Springer Series in Perception Engineering | | 圖書(shū)封面 |  | | 影響因子 | Since the early days of computers, machine learning and automatic programming have attracted researchers in computer science and related fields, particularly pattern recognition and automatic control theory. Most of the learning concepts in machine perception have been inspired by pattern recognition approaches that rely on statistical techniques. These statistical techniques have applicability in limited recognition tasks. Automatic programming in perception systems has generally been limited to interfaces that allow easy specification of the task using natural language. Clearly, machine learning and automatic programming can make percep- tion systems powerful and easy to use. Vogt‘s book addresses both these tasks in the context of machine vision. He uses morphological operations to implement his approach which was developed for solving the figure-ground problem in images. His system selects the correct se- quence of operators to accept or reject pixels for fmding objects in an image. The sequence of operators is selected after a user specifies what the correct objects are. On the surface it may appear that the problem solved by the system is not very interesting, however, the co | | Pindex | Book 1989 |
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