Institution
Panasonic
Company•Kadoma, Ôsaka, Japan•
About: Panasonic is a company organization based out in Kadoma, Ôsaka, Japan. It is known for research contribution in the topics: Signal & Layer (electronics). The organization has 49129 authors who have published 71118 publications receiving 942756 citations. The organization is also known as: Panasonikku Kabushiki-gaisha & Panasonic.
Topics: Signal, Layer (electronics), Electrode, Terminal (electronics), Transmission (telecommunications)
Papers published on a yearly basis
Papers
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03 Sep 2003TL;DR: This work defines five metrics for measuring a component's understandability, adaptability, and portability, with confidence intervals that were set by statistical analysis of a number of JavaBeans components, and provides aReusability metric by combining these metrics based on a reusability model.
Abstract: In component-based software development, it is necessary to measure the reusability of components in order to realize the reuse of components effectively. There are some product metrics for measuring the reusability of object-oriented software. However, in application development with reuse, it is difficult to use conventional metrics because the source codes of components cannot be obtained, and these metrics require analysis of source codes. We propose a metrics suite for measuring the reusability of such black-box components based on limited information that can be obtained from the outside of components without any source codes. We define five metrics for measuring a component's understandability, adaptability, and portability, with confidence intervals that were set by statistical analysis of a number of JavaBeans components. Moreover, we provide a reusability metric by combining these metrics based on a reusability model. As a result of evaluation experiments, it is found that our metrics can effectively identify black-box components with high reusability.
225 citations
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03 Apr 1995TL;DR: In this paper, a head-up display unit equipped at least with transparent and flat image information display means, light supply means for supplying light to the light irradiating means, image-display control means for controlling image display, and light supply control mean for controlling light supply.
Abstract: A head up display unit equipped at least with transparent and flat image information display means, transparent and flat light irradiating means arranged in an opposed and close contact relationship with the image information display means, light supply means for supplying light to the light irradiating means, image-display control means for controlling image display, and light-supply control means for controlling light supply. The display unit is a compact head up display unit which can be used in any place in the interior of an automobile.
225 citations
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11 May 2011TL;DR: In this article, a nitride semiconductor device is defined as: a first semiconductor layer made of first nitride, a second semiconductor, made of second nitride having a bandgap wider than that of the first, a control layer selectively formed on, or above, an upper portion of the second, and a third semiconductor having a p-type conductivity.
Abstract: A nitride semiconductor device includes: a first semiconductor layer made of first nitride semiconductor; a second semiconductor layer formed on a principal surface of the first semiconductor layer and made of second nitride semiconductor having a bandgap wider than that of the first nitride semiconductor; a control layer selectively formed on, or above, an upper portion of the second semiconductor layer and made of third nitride semiconductor having a p-type conductivity; source and drain electrodes formed on the second semiconductor layer at respective sides of the control layer; a gate electrode formed on the control layer; and a fourth semiconductor layer formed on a surface of the first semiconductor layer opposite to the principal surface, having a potential barrier in a valence band with respect to the first nitride semiconductor and made of fourth nitride semiconductor containing aluminum.
224 citations
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13 Jul 1989TL;DR: In this article, a method of and an apparatus for managing defective sectors in an information recording medium such as a write-once optical disk and rewritable optical disk in which many defective sectors may be generated and unevenly distributed is presented.
Abstract: A method of and an apparatus for managing defective sectors in an information recording medium such as a write-once optical disk and rewritable optical disk in which many defective sectors may be generated and unevenly distributed. In the medium, alternative zones are formed which are composed of: a prime area for recording user data the capacity of which is variable according to the volume capacity and partition capacity and the occurrence rate of defective sectors; a primary spare area for recording alternative sectors; and a primary defect list area for recording a primary defect list. Many defective sectors are managed in the units of alternative zones. When defective sectors cannot be substituted in an alternative zone (e.g., when defective sectors are locally concentrated), defective sectors are managed hierarchically using a secondary alternative area, thereby reducing the amount of information to be handled for the management of defective sectors. Therefore, the size of the apparatus can be reduced, and defective sectors can be rapidly searched.
224 citations
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01 Jun 2018
TL;DR: Qualitative and quantitative experiments on both controlled and in-the-wild benchmarks demonstrate the superiority of the proposed Pose Invariant Model for face recognition in the wild over the state of thearts.
Abstract: Pose variation is one key challenge in face recognition. As opposed to current techniques for pose invariant face recognition, which either directly extract pose invariant features for recognition, or first normalize profile face images to frontal pose before feature extraction, we argue that it is more desirable to perform both tasks jointly to allow them to benefit from each other. To this end, we propose a Pose Invariant Model (PIM) for face recognition in the wild, with three distinct novelties. First, PIM is a novel and unified deep architecture, containing a Face Frontalization sub-Net (FFN) and a Discriminative Learning sub-Net (DLN), which are jointly learned from end to end. Second, FFN is a well-designed dual-path Generative Adversarial Network (GAN) which simultaneously perceives global structures and local details, incorporated with an unsupervised cross-domain adversarial training and a "learning to learn" strategy for high-fidelity and identity-preserving frontal view synthesis. Third, DLN is a generic Convolutional Neural Network (CNN) for face recognition with our enforced cross-entropy optimization strategy for learning discriminative yet generalized feature representation. Qualitative and quantitative experiments on both controlled and in-the-wild benchmarks demonstrate the superiority of the proposed model over the state-of-the-arts.
222 citations
Authors
Showing all 49132 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yang Yang | 171 | 2644 | 153049 |
Hideo Hosono | 128 | 1549 | 100279 |
Shuicheng Yan | 123 | 810 | 66192 |
Akira Yamamoto | 117 | 1999 | 74961 |
Adam Heller | 111 | 381 | 41063 |
Tadashi Kokubo | 104 | 557 | 49042 |
Masatoshi Kudo | 100 | 1324 | 53482 |
Héctor D. Abruña | 98 | 585 | 38995 |
Duong Nguyen | 98 | 674 | 47332 |
Henning Sirringhaus | 96 | 467 | 50846 |
Chao Yang Wang | 95 | 307 | 26857 |
George G. Malliaras | 94 | 382 | 28533 |
Masaki Takata | 90 | 594 | 28478 |
Darrell G. Schlom | 88 | 641 | 41470 |
Thomas A. Moore | 87 | 437 | 30666 |