1.4k citations
- Kyoto UniversityJP15 papers
- The University of TokyoJP14 papers
- Tokyo Institute of TechnologyJP7 papers
- University of TsukubaJP6 papers
- National Institute of Advanced Industrial Science and TechnologyJP5 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)DE3 papers
- Institut polytechnique de GrenobleFR3 papers
- Japan Atomic Energy AgencyJP3 papers
- Kyoto College of Graduate Studies for InformaticsJP3 papers
- Kyushu UniversityJP3 papers
- Nara Institute of Science and TechnologyJP3 papers
14 papers · 1 filter
Binary classification with ambiguous training data
Naoya Otani, Yosuke Otsubo, Tetsuya Koike +1
In supervised learning, we often face with ambiguous (A) samples that are difficult to label even by domain experts. In this paper, we consider a binary classification problem in t…
Augmenting Images for ASR and TTS through Single-loop and Dual-loop Multimodal Chain Framework
Johanes Effendi, Andros Tjandra, Sakriani Sakti +1
Previous research has proposed a machine speech chain to enable automatic speech recognition (ASR) and text-to-speech synthesis (TTS) to assist each other in semi-supervised learni…
Lengths of maximal green sequences for tame path algebras
Ryoichi Kase, Ken Nakashima
In this paper, we study the maximal length of maximal green sequences for quivers of type and by using the theory of tilting mutat…
Leveraging Tacit Information Embedded in CNN Layers for Visual Tracking
Kourosh Meshgi, Maryam Sadat Mirzaei, Shigeyuki Oba
Different layers in CNNs provide not only different levels of abstraction for describing the objects in the input but also encode various implicit information about them. The activ…
Learning from Multimodal and Multitemporal Earth Observation Data for Building Damage Mapping
Bruno Adriano, Naoto Yokoya, Junshi Xia +4
Earth observation technologies, such as optical imaging and synthetic aperture radar (SAR), provide excellent means to monitor ever-growing urban environments continuously. Notably…
Screening Rules and its Complexity for Active Set Identification
Eugene Ndiaye, Olivier Fercoq, Joseph Salmon
Screening rules were recently introduced as a technique for explicitly identifying active structures such as sparsity, in optimization problem arising in machine learning. This has…