#### Filter Results:

- Full text PDF available (1)

#### Publication Year

1972

1998

- This year (0)
- Last 5 years (0)
- Last 10 years (0)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

Learn More

- Tsunehiro Aibara, Takehiro Mabuchi
- MVA
- 1998

This paper deals with a fundamental method of automatic assessment of the appearance of seam puckers (SP) on suits. Taking the fractal dimensions of SPs as features, we process the problem as pattern recognition. Twenty suits were used for the evaluation experiment and we could obtain a result close to the human inspection. The result was also compared to… (More)

- Kenji Murakami, Tsunehiro Aibara
- IEEE Transactions on Pattern Analysis and Machine…
- 1981

The purpose of this correspondence is to propose a new construction method of distributed associative memory which operates with discrete-valued signals. In this method, memorized pairs of vectors (cue vectors and data vectors) are recorded in the form of a matrix W and a vector T. From an input vector X, the data vector is recalled by an operation u(XW +… (More)

- Kenji Murakami, Tsunehiro Aibara
- IEEE Trans. Systems, Man, and Cybernetics
- 1987

- Kenji Murakami, Tsunehiro Aibara
- IEEE Trans. Systems, Man, and Cybernetics
- 1989

- Tsunehiro Aibara, Michihiro Akagi
- IEEE Trans. Computers
- 1972

- Kenji Murakami, Tsunehiro Aibara
- DASFAA
- 1989

- Kenji Murakami, Yasuhiro Yamajo, Tsunehiro Aibara
- Systems and Computers in Japan
- 1989

- Hiroyuki Yamada, Tetsuo Kobashi, Tsunehiro Aibara
- IEICE Transactions
- 1995

- Noboru Babaguchi, Tsunehiro Aibara
- Pattern Recognition
- 1987

-The shape analysis of a binary picture is of great importance for pictorial pattern recognition. In this paper, we propose a useful geometric feature parameter called curvedness. Curvedness represents which lines are dominant in a binary picture, straight or curved. Our algorithm for measuring curvedness is based on the relationship between the distance to… (More)

- Masanori Izumida, Kenji Murakami, Tsunehiro Aibara
- Systems and Computers in Japan
- 1992

In this paper, we discuss a method for analyzing the energy function of a Hopfield-type neural network. In order to analyze the energy function which solves the given minimization problem, or simply, the problem, we define the standard form of the energy function. In general, a multidimensional energy function is complex, and it is difficult to investigate… (More)

- ‹
- 1
- ›