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Institution

Toyota

CompanySafenwil, Switzerland
About: Toyota is a company organization based out in Safenwil, Switzerland. It is known for research contribution in the topics: Internal combustion engine & Exhaust gas. The organization has 40032 authors who have published 55003 publications receiving 735317 citations. The organization is also known as: Toyota Motor Corporation & Toyota Jidosha KK.


Papers
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Proceedings ArticleDOI
23 Jun 2013
TL;DR: This paper presents a discriminative method based on a Least-Squares Support Vector Machine formulation that addresses the issue of transferring to the new class and preserving what has already been learned on the source models when learning a new class.
Abstract: Since the seminal work of Thrun [16], the learning to learn paradigm has been defined as the ability of an agent to improve its performance at each task with experience, with the number of tasks. Within the object categorization domain, the visual learning community has actively declined this paradigm in the transfer learning setting. Almost all proposed methods focus on category detection problems, addressing how to learn a new target class from few samples by leveraging over the known source. But if one thinks of learning over multiple tasks, there is a need for multiclass transfer learning algorithms able to exploit previous source knowledge when learning a new class, while at the same time optimizing their overall performance. This is an open challenge for existing transfer learning algorithms. The contribution of this paper is a discriminative method that addresses this issue, based on a Least-Squares Support Vector Machine formulation. Our approach is designed to balance between transferring to the new class and preserving what has already been learned on the source models. Extensive experiments on subsets of publicly available datasets prove the effectiveness of our approach.

157 citations

Journal ArticleDOI
TL;DR: In this paper, it was shown that chlorides in the cation (Mg2(μ-Cl)3·6THF)+ are a major culprit for corrosion.
Abstract: Chloride containing magnesium electrolytes are corrosive towards non noble metals. Currently the development of non-corrosive magnesium electrolytes is a key challenge on the road to a rechargeable magnesium battery. The component responsible for corrosion of magnesium electrolytes has not been previously elucidated. Here we clarify that chlorides in the cation (Mg2(μ-Cl)3·6THF)+ are a major culprit for corrosion. We also corroborate the feasibility of ion exchange reactions as a suitable synthetic approach towards magnesium electrolytes which do not contain the cation (Mg2(μ-Cl)3·6THF)+. Our results indicate that magnesium organoborates are an interesting class of magnesium electrolytes which undergo magnesium deposition and dissolution and are non-corrosive in nature at high voltages.

156 citations

Journal ArticleDOI
TL;DR: In this paper, the 10th International Symposium on Metal-Hydrogen Systems, Fundamentals and Applications, Lahaina, HIGM Res & Dev, Hawaii Hydrogen Carriers LLC; Hy Energy, LLC; Jet Propuls Lab; NIST Ctr Neutron Res; Suzuki Shokan Co, Ltd; Toyota Motor Sales Reference EPFL-ARTICLE-205982

156 citations

Patent
17 Sep 1996
TL;DR: In this paper, a side impact air bag is activated at the time of side impact such that a sewn portion of a seat surface layer, which is formed by sewing a front seat surface surface layer for covering the front of the seat back to a side-sensor surface layer to cover the side of the front seat back, breaks and an air bag body inflates between a side portion of the vehicle body and the passenger's side of a vehicle occupant.
Abstract: A seat structure having a side impact air bag apparatus, constructed such that the air bag apparatus, which is integrated into a side portion of a seat back which side portion opposes a vehicle door, is activated at the time of a side impact such that a sewn portion of a seat surface layer, which is formed by sewing a front seat surface layer for covering the front of the seat back to a side seat surface layer for covering the side of the seat back, breaks and an air bag body inflates between a side portion of a vehicle body and the side of a vehicle occupant, comprising a sheet member provided inside the side seat surface layer integrally with the side seat surface layer, the sheet member being harder to stretch than the side seat surface layer, and one end of the sheet member being sewn to the sewn portion; and a fixing member provided inside the seat back, the fixing member being engaged with another end of the sheet member which is provided on the opposite side of the one end of the sheet member.

156 citations

Patent
05 Dec 2014
TL;DR: In this paper, a smart necklace includes a body defining at least one cavity and having a neck portion and first and second side portions, which is configured to detect image data including depth information corresponding to a surrounding environment of the smart necklace.
Abstract: A smart necklace includes a body defining at least one cavity and having a neck portion and first and a second side portions. The necklace includes a pair of stereo cameras that is configured to detect image data including depth information corresponding to a surrounding environment of the smart necklace. The necklace further includes a positioning sensor configured to detect positioning data corresponding to a positioning of the smart necklace. The necklace includes a non-transitory memory positioned in the at least one cavity and configured to store map data and object data. The smart necklace also includes a processor positioned in the at least one cavity, coupled to the pair of stereo cameras, the positioning sensor and the non-transitory memory. The processor is configured to determine output data based on the image data, the positioning data, the map data and the object data.

155 citations


Authors

Showing all 40045 results

NameH-indexPapersCitations
Derek R. Lovley16858295315
Edward H. Sargent14084480586
Shanhui Fan139129282487
Susumu Kitagawa12580969594
John B. Buse117521101807
Meilin Liu11782752603
Zhongfan Liu11574349364
Wolfram Burgard11172864856
Douglas R. MacFarlane11086454236
John J. Leonard10967646651
Ryoji Noyori10562747578
Stephen J. Pearton104191358669
Lajos Hanzo101204054380
Masashi Kawasaki9885647863
Andrzej Cichocki9795241471
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
202232
2021942
20201,846
20192,981
20182,541