Deep Learning and Computer Vision: Guidelines and Special Issues
被引:0
|
作者:
Grewe, Lynne
论文数: 0引用数: 0
h-index: 0
机构:
Calif State Univ East Bay, Comp Sci, 25800 Carlos Bee Blvd, Hayward, CA 94542 USACalif State Univ East Bay, Comp Sci, 25800 Carlos Bee Blvd, Hayward, CA 94542 USA
Grewe, Lynne
[1
]
论文数: 引用数:
h-index:
机构:
Stevenson, Garrett
[1
]
机构:
[1] Calif State Univ East Bay, Comp Sci, 25800 Carlos Bee Blvd, Hayward, CA 94542 USA
来源:
SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXVII
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2018年
/
10646卷
关键词:
Deep Learning;
Computer Vision;
Multi-Modal Deep Learning;
Temporal Networks;
D O I:
暂无
中图分类号:
O43 [光学];
学科分类号:
070207 ;
0803 ;
摘要:
The catapult of Computer Vision into recent societal prominence is represented by advancements in self-driving cars, drone autonomy, and cities of the future. Central to these advancements are the developments of Deep Learning with Computer Vision to tackle the important tasks of object classification and localization. This paper surveys some of the current research and presents current guidelines for working in computer vision with deep learning. Additionally, special topics are highlighted including Multi-Modal Vision with Deep Learning and Temporal Networks.