no code implementations • COLING 2022 • Jingyi You, Dongyuan Li, Manabu Okumura, Kenji Suzuki
Automated radiology report generation aims to generate paragraphs that describe fine-grained visual differences among cases, especially those between the normal and the diseased.
1 code implementation • 5 Dec 2022 • Naoki Matsunaga, Masato Ishii, Akio Hayakawa, Kenji Suzuki, Takuya Narihira
Our goal is to develop fine-grained real-image editing methods suitable for real-world applications.
1 code implementation • 3 Aug 2022 • Diego Paez-Granados, Yujie He, David Gonon, Dan Jia, Bastian Leibe, Kenji Suzuki, Aude Billard
Autonomous navigation in highly populated areas remains a challenging task for robots because of the difficulty in guaranteeing safe interactions with pedestrians in unstructured situations.
1 code implementation • 9 Jul 2021 • Lingfeng Wang, Shisen Wang, Jin Qi, Kenji Suzuki
To tackle this problem, this paper presents a semi-supervised model with a mean teacher framework to leverage additional unlabeled data.
1 code implementation • 22 Mar 2021 • Kenji Suzuki, Yoshiyuki Kobayashi, Takuya Narihira
Moreover, our simple and general proposed method to calculate influence scores is available on our auto ML tool without programing, Neural Network Console.
1 code implementation • 12 Feb 2021 • Takuya Narihira, Javier Alonsogarcia, Fabien Cardinaux, Akio Hayakawa, Masato Ishii, Kazunori Iwaki, Thomas Kemp, Yoshiyuki Kobayashi, Lukas Mauch, Akira Nakamura, Yukio Obuchi, Andrew Shin, Kenji Suzuki, Stephen Tiedmann, Stefan Uhlich, Takuya Yashima, Kazuki Yoshiyama
While there exist a plethora of deep learning tools and frameworks, the fast-growing complexity of the field brings new demands and challenges, such as more flexible network design, speedy computation on distributed setting, and compatibility between different tools.
no code implementations • 20 Aug 2020 • Monica Perusquia-Hernandez, Felix Dollack, Chun Kwang Tan, Shushi Namba, Saho Ayabe-Kanamura, Kenji Suzuki
We quantified the co-occurrence and timing of AU6 and AU12 in posed and spontaneous smiles using the human-coded labels, and for comparison, using the continuous CV-labels.