Deep Learning-Based Image Recognition for Autonomous Driving
自動運転のための深層学習による画像認識技術
- Delivery
- Available on this site
- Format
- Price
- Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880
- Publication code
- 20224579
- Paper/Info type
- Journal of Society of Automotive Engineers of Japan
Vol.76 No.11
- Pages
- 58-63(Total 6 p)
- Date of publication
- Nov 2022
- Publisher
- JSAE
- Language
- Japanese
Detailed Information
| Category(J) | CASEを支える最新カーエレクトロニクス Translation |
|---|---|
| Category(E) | Latest Car Electronics supporting CASE |
| Author(J) | 1) 藤吉 弘亘 |
| Author(E) | 1) Hironobu Fujiyoshi |
| Affiliation(J) | 1) 中部大学 |
| Abstract(J) | 2010年以前の画像認識分野では，研究者が設計したハンドクラフト特徴と機械学習手法を組み合わせることで，さまざまな画像認識タスクを実現していた． 2010年以降は，深層学習を用いた画像認識手法が数多く提案され，深層学習が登場する前の手法より大幅な認識性能の向上を達成した．そこで本稿では，深層学習が画像認識にどのように適用されているかを説明するとともに，自動運転に向けた深層学習の最新動向について解説する． Translation |
| Abstract(E) | Various image recognition tasks were handled in the image recognition field prior to 2010 by combining image local features manually designed by researchers（called handcrafted features） and machine learning method. After entering the 2010, However, many image recognition methods that use deep learning have been proposed. The image recognition methods using deep learning are far superior to the methods used prior to the appearance of deep learning in general object recognition competitions. Hence, this paper will explain how deep learning is applied to the field of image recognition, and will also explain the latest trends of deep learning-for autonomous driving. |
