Zobrazeno 1 - 10
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pro vyhledávání: '"TAKEUCHI, Masaru"'
Autor:
Abraham, Prema, Aderman, Christopher, Akiyama, Kunihiko, Alfaro, Daniel V., Ali, Fareed A., Amini, Payam, Anzalotta, Andres Emanuelli, Bátor, György, Batlle, Ivan, Berger, Adam, Bhandari, Ramanath, Bridges, William, Brinkmann, Christian, Brown, Jamin, Burgess, Stuart, Calzada, Jorge, Capone Jr., Antonio, Cervena, Dana, Charles, Steven, Chaudhry, Nauman, Chow, David, Clark, W. Lloyd, Conrad III, Paul, Cunningham, Matthew, Dadgostar, Hajir, Dessouki, Amr, Deupree, Dana, Devine, Christopher, Eichenbaum, David, Ernest, Jan, Feltgen, Nicolas, Fenberg, Moss, Ferrone, Philip, Frenkel, Ronald, Friedman, Scott, Gasperini, Julie, Gerstenblith, Adam, Ghorayeb, Ghassan, Giunta, Michel, Goff, Mitchell, Golas, Liliya, Googe Jr., Joseph M., Goren Fein, Jordana, Hagedorn, Curtis, Hagiwara, Akira, Hahn, Paul, Hairston, Richard, Handza, Jason, Hau, Vivienne, Hayashi, Ken, Heier, Jeffrey, Hershberger, Vrinda, Higgins, Patrick, Hirano, Yoshio, Honda, Shigeru, Ikegami, Yasuko, Ishida, Yuichiro, Ishikawa, Isao, Ishii, Kiyoshi, Jablon, Eric P., Jain, Atul, Kaji, Yuichi, Kapoor, Kapil, Kerényi, Ágnes, Kimura, Kazuhiro, Kishino, Genichiro, Kiss, Katalin, Kitaoka, Takashi, Klancnik, James M., Kobayashi, Namie, Kogo, Jiro, Korda, Vladimir, Kruger, Erik, Kusuhara, Sentaro, Lara, Wilfredo, Laud, Ketan, Lee, Seong, Luu, James, Marcus, Dennis, Mein, Calvin, Meleth, Annal, Milibák, Tibor, Mitamura, Yoshinori, Murata, Toshinori, Noge, Sumiyo, Onoe, Hajime, Osher, James, Papp, András, Parschauer, Justin, Patel, Sugat, Patel, Sunil, Pezda, Matthew, Pirouz, Ashkan, Prasad, Pradeep, Punjabi, Omar, Rao, Llewelyn, Roe, Richard, Schadlu, Ramin, Schneider, Eric, Shah, Ankur, Shah, Milan, Shah, Sandeep, Shah, Sumit, Sharma, Ashish, Sheth, Veeral, Shimura, Masahiko, Singerman, Lawrence, Spital, Georg, Stoltz, Robert, Suan, Eric, Suzuma, Kiyoshi, Takahashi, Hidenori, Takamura, Yoshihiro, Takeuchi, Masaru, Tan, Jeffrey, Thomas, Benjamin, Tóth,-Molnár, Edit, Ueda, Tetsuo, Ushida, Hiroaki, Vajas, Attila, Varma, Deepali, Varsányi, Balázs, Veith, Miroslav, Weber, Pamela, Wee, Raymond, Williams, Geoff, Yamada, Haruhiko, Yonekawa, Yoshihiro, Yoshida, Shigeo, Brown, David M, Boyer, David S, Do, Diana V, Wykoff, Charles C, Sakamoto, Taiji, Win, Peter, Joshi, Sunir, Salehi-Had, Hani, Seres, András, Berliner, Alyson J, Leal, Sergio, Vitti, Robert, Chu, Karen W, Reed, Kimberly, Rao, Rohini, Cheng, Yenchieh, Sun, Wei, Voronca, Delia, Bhore, Rafia, Schmidt-Ott, Ursula, Schmelter, Thomas, Schulze, Andrea, Zhang, Xin, Hirshberg, Boaz, Yancopoulos, George D, Sivaprasad, Sobha *
Publikováno v:
In The Lancet 23-29 March 2024 403(10432):1153-1163
Autor:
Pichi, Francesco, Smith, Scott D., Goldstein, Debra A., Baddar, Dina, Gerges, Terese K.A., Janetos, Timothy M., Ruiz-Cruz, Matilde, Elena Concha-del-Río, Luz, Maruyama, Kazuichi, Carina ten Berge, Josianne, Rombach, Saskia M., Cimino, Luca, Bolletta, Elena, Miserocchi, Elisabetta, Scandale, Pierluigi, Serafino, Massimiliano, Camicione, Paola, Androudi, Sofia, Gonzalez-Lopez, Julio J., Lim, Lyndell L., Singh, Nandini, Gupta, Vishali, Gupta, Nikita, Amer, Radgonde, Dodds, Emilio M., Inchauspe, Sebastian, Munk, Marion R., Donicova, Emilia, Carreño, Ester, Takeuchi, Masaru, Chee, Soon-Phaik, Chew, Milton C., Agarwal, Aniruddha, Schlaen, Ariel, Gómez, Ramiro A., Couto, Cristobal A., Khairallah, Moncef, Neri, Piergiorgio
Publikováno v:
In American Journal of Ophthalmology February 2024 258:87-98
Autor:
Takeuchi, Masaru1 (AUTHOR) kankan@ndmc.ac.jp, Kanda, Takayuki1 (AUTHOR), Harimoto, Kozo1 (AUTHOR), Sora, Daisuke1 (AUTHOR), Okazawa, Rina1 (AUTHOR), Sato, Tomohito1 (AUTHOR)
Publikováno v:
Journal of Clinical Medicine. Jun2024, Vol. 13 Issue 11, p3252. 15p.
Learned image compression (LIC) has reached the traditional hand-crafted methods such as JPEG2000 and BPG in terms of the coding gain. However, the large model size of the network prohibits the usage of LIC on resource-limited embedded systems. This
Externí odkaz:
http://arxiv.org/abs/2007.04684
This paper enhances the intra prediction by using multiple neural network modes (NM). Each NM serves as an end-to-end mapping from the neighboring reference blocks to the current coding block. For the provided NMs, we present two schemes (appending a
Externí odkaz:
http://arxiv.org/abs/2005.02973
Lossless image compression is an important task in the field of multimedia communication. Traditional image codecs typically support lossless mode, such as WebP, JPEG2000, FLIF. Recently, deep learning based approaches have started to show the potent
Externí odkaz:
http://arxiv.org/abs/2002.01657
Image compression is a fundamental research field and many well-known compression standards have been developed for many decades. Recently, learned compression methods exhibit a fast development trend with promising results. However, there is still a
Externí odkaz:
http://arxiv.org/abs/2001.01568
Akademický článek
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Autor:
Liu, Chao, Sun, Heming, Chen, Junan, Cheng, Zhengxue, Takeuchi, Masaru, Katto, Jiro, Zeng, Xiaoyang, Fan, Yibo
In this paper, a dual learning-based method in intra coding is introduced for PCS Grand Challenge. This method is mainly composed of two parts: intra prediction and reconstruction filtering. They use different network structures, the neural network-b
Externí odkaz:
http://arxiv.org/abs/1911.09857
In this paper, we provide a detailed description on our approach designed for CVPR 2019 Workshop and Challenge on Learned Image Compression (CLIC). Our approach mainly consists of two proposals, i.e. deep residual learning for image compression and s
Externí odkaz:
http://arxiv.org/abs/1906.09731