Dr. Hirokazu Nosato Profile

Dr. Hirokazu Nosato

Team Leader at AIST Tsukuba Headquaters

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Author

Publications (10)

Proceedings Article | 3 April 2024 Poster + Paper

Artificial intelligence in cystoscopic bladder cancer classification based on transfer learning with a pre-trained convolutional neural network without natural images

Ryuunosuke Kounosu, Wonjik Kim, Atsushi Ikeda, Hirokazu Nosato, Yuu Nakajima

Proceedings Volume 12927, 1292727 (2024) https://doi.org/10.1117/12.3005605

KEYWORDS: Artificial intelligence, Image classification, Machine learning, Tumors, Diagnostics, Bladder cancer, Deep learning

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Proceedings Article | 20 April 2021 Paper

Tumor detection from breast ultrasound images using mammary gland attentive U-Net

Kaiwen Yang, Aiga Suzuki, Jiaxing Ye, Hirokazu Nosato, Ayumi Izumori, Hidenori Sakanashi

Proceedings Volume 11792, 1179202 (2021) https://doi.org/10.1117/12.2590073

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Proceedings Article | 7 October 2019 Presentation + Paper

Object detection in satellite images based on human cooperative semi-self-training

Kazuki Uehara, Hirokazu Nosato, Masahiro Murakawa, Hidenori Sakanashi

Proceedings Volume 11155, 111550P (2019) https://doi.org/10.1117/12.2533004

KEYWORDS: Earth observing sensors, Satellite imaging, Satellites, Statistical modeling, Convolutional neural networks, Data modeling, Performance modeling, Landsat, Machine learning, Feature extraction

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Proceedings Article | 20 March 2015 Paper

A content-based image retrieval method for optical colonoscopy images based on image recognition techniques

Hirokazu Nosato, Hidenori Sakanashi, Eiichi Takahashi, Masahiro Murakawa

Proceedings Volume 9414, 94141E (2015) https://doi.org/10.1117/12.2082368

KEYWORDS: Feature extraction, Image retrieval, Image enhancement, Content based image retrieval, Databases, Diagnostics, Medical imaging, Image processing, Inflammation, Colon

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SPIE Journal Paper | 6 February 2014

Hotspot prevention and detection method using an image-recognition technique based on higher-order local autocorrelation

Hirokazu Nosato, Hidenori Sakanashi, Eiichi Takahashi, Masahiro Murakawa, Tetsuaki Matsunawa, Shimon Maeda, Satoshi Tanaka

JM3, Vol. 13, Issue 01, 011007, (February 2014) https://doi.org/10.1117/12.10.1117/1.JMM.13.1.011007

KEYWORDS: Lithography, Feature extraction, Photomasks, Semiconducting wafers, Design for manufacturing, Data modeling, Semiconductors, Geometrical optics, Binary data, Image classification

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Proceedings Article | 13 March 2012 Paper

Generator of predictive verification pattern using vision system based on higher-order local autocorrelation

Tetsuaki Matsunawa, Shimon Maeda, Hirotaka Ichikawa, Shigeki Nojima, Satoshi Tanaka, Shoji Mimotogi, Hirokazu Nosato, Hidenori Sakanashi, Masahiro Murakawa, Eiichi Takahashi

Proceedings Volume 8326, 832615 (2012) https://doi.org/10.1117/12.916306

KEYWORDS: Lithography, Feature extraction, Semiconducting wafers, Resolution enhancement technologies, Statistical analysis, Lithographic illumination, Photomasks, Pattern recognition, Diffraction, Geometrical optics

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Proceedings Article | 5 April 2011 Paper

Hotspot detection using image pattern recognition based on higher-order local auto-correlation

Shimon Maeda, Tetsuaki Matsunawa, Ryuji Ogawa, Hirotaka Ichikawa, Kazuhiro Takahata, Masahiro Miyairi, Toshiya Kotani, Shigeki Nojima, Satoshi Tanaka, Kei Nakagawa, Tamaki Saito, Shoji Mimotogi, Soichi Inoue, Hirokazu Nosato, Hidenori Sakanashi, Takumi Kobayashi, Masahiro Murakawa, Tetsuya Higuchi, Eiichi Takahashi, Nobuyuki Otsu

Proceedings Volume 7974, 79740X (2011) https://doi.org/10.1117/12.881193

KEYWORDS: Lithography, Pattern recognition, Computer aided design, Feature extraction, Intelligence systems, Silicon, Photomasks, Image processing, Visualization, Graphic design

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Proceedings Article | 10 March 2010 Paper

Ultimately accurate SRAF replacement for practical phases using an adaptive search algorithm based on the optimal gradient method

Shimon Maeda, Hirokazu Nosato, Tetsuaki Matsunawa, Masahiro Miyairi, Shigeki Nojima, Satoshi Tanaka, Hidenori Sakanashi, Masahiro Murakawa, Tamaki Saito, Tetsuya Higuchi, Soichi Inoue

Proceedings Volume 7640, 764018 (2010) https://doi.org/10.1117/12.846345

KEYWORDS: SRAF, Lithography, Photomasks, Critical dimension metrology, Algorithm development, Computer simulations, Manufacturing, Image resolution, Optical lithography, Switching

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SRAF (Sub Resolution Assist Feature) technique has been widely used for DOF enhancement. Below 40nm design node, even in the case of using the SRAF technique, the resolution limit is approached due to the use of hyper NA imaging or low k1 lithography conditions especially for the contact layer. As a result, complex layout patterns or random patterns like logic data or intermediate pitch patterns become increasingly sensitive to photo-resist pattern fidelity. This means that the need for more accurate resolution technique is increasing in order to cope with lithographic patterning fidelity issues in low k1 lithography conditions. To face with these issues, new SRAF technique like model based SRAF using an interference map or inverse lithography technique has been proposed. But these approaches don't have enough assurance for accuracy or performance, because the ideal mask generated by these techniques is lost when switching to a manufacturable mask with Manhattan structures. As a result it might be very hard to put these things into practice and production flow. In this paper, we propose the novel method for extremely accurate SRAF placement using an adaptive search algorithm. In this method, the initial position of SRAF is generated by the traditional SRAF placement such as rule based SRAF, and it is adjusted by adaptive algorithm using the evaluation of lithography simulation. This method has three advantages which are preciseness, efficiency and industrial applicability. That is, firstly, the lithography simulation uses actual computational model considering process window, thus our proposed method can precisely adjust the SRAF positions, and consequently we can acquire the best SRAF positions. Secondly, because our adaptive algorithm is based on optimal gradient method, which is very simple algorithm and rectilinear search, the SRAF positions can be adjusted with high efficiency. Thirdly, our proposed method, which utilizes the traditional SRAF placement, is easy to be utilized in the established workflow. These advantages make it possible to give the traditional SRAF placement a new breath of life for low k1.

Proceedings Article | 1 November 2007 Paper

Improving the efficiency of pattern extraction for character projection lithography using OPC optimization

Hirokazu Nosato, Tetsuaki Matsunawa, Hidenori Sakanashi, Masahiro Murakawa, Tetsuya Higuchi

Proceedings Volume 6730, 67304G (2007) https://doi.org/10.1117/12.746687

KEYWORDS: Optical proximity correction, Photomasks, Algorithm development, Logic devices, Optimization (mathematics), Lithography, Projection lithography, Electron beam lithography, Logic, Electron beams

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Proceedings Article | 9 November 2005 Paper

The novel approach for optical proximity correction using genetic algorithms

Tetsuaki Matsunawa, Hirokazu Nosato, Hidenori Sakanashi, Masahiro Murakawa, Nobuharu Murata, Tsuneo Terasawa, Toshihiko Tanaka, Nobuyuki Yoshioka, Osamu Suga, Tetsuya Higuchi

Proceedings Volume 5992, 599254 (2005) https://doi.org/10.1117/12.632041

KEYWORDS: Optical proximity correction, Genetic algorithms, Photomasks, Model-based design, Genetics, Optimization (mathematics), Semiconductors, Semiconducting wafers, Wafer-level optics, Computer simulations

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Showing 5 of 10 publications

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