VII. DEEP LEARNING TRAINING AT EDGE 当前在云数据中心的DL培训(无论是否分发),即云培训或云边缘培训[47],即在边缘处对培训数据进行预处理,然后传输到云,并不适合所有类型的DL服务,特别是对于需要局部性和持续训练的DL模型。此外,如果需要将大量数据从分布式终端设备或边缘节点连续传输到云,则将消耗大量的通信资源...
3)结构边缘检测包括: SE (structured forests edge detection) algorithm [10]。 虽然手工设计的算法已经成果显著,但其限制也是很明显的。 基于深度学习 的方法:2015 HED [12] ; in 2015, Ou et al. [13] proposed to apply full convolution to semantic segmentation, which lays the foundation for full co...
The adaptive optimization of edge detection was realized by combining with deep learning algorithm. The adaptive optimization in the process of edge detection was realized by combining with the deep learning algorithm. The experimental results show that the three-dimensional reconstruction accuracy of the...
[10] J. Ren, Y. Guo, D. Zhang et al. Distributed and Efficient Object Detection in Edge Computing: Challenges and Solutions[J]. IEEE Network, 2018, 32 ( 6 ) : 137 - 143. [11] C. Szegedy, Wei Liu, Yangqing Jia et al. Going deeper with convolutions[C]. 2015 IEEE Conference on...
Later, algorithms such as Structured Forest for Fast Edge Detection, which use machine learning with hand-crafted features, grew in popularity as they were more accurate and relatively faster than their predecessors[3]. In the last few years, with advancements in deep learning, many CNN-based ...
自动驾驶汽车需要复杂的传感器(雷达,激光雷达,高分辨率相机等)来不断捕获汽车执行自动驾驶任务所需的环境信息。这需要一套高性能嵌入式计算(HPEC)系统 ,这些系统能够处理大量数据,与传感器交换这些数据并应用Edge AI(人工智能)和深度学习算法 来实时训练车辆。
Raspberry Pi 3 has a quad-core ARM processor at 1.2 GHz with 1 GB of RAM. The available bandwidth between the edge server and the mobile device is controlled by the WonderShaper [10] tool. As for the deep learning framework, we choose Chainer [11] that can well support branchy DNN ...
A deep learning framework with edge computing for severity level detection of diabetic retinopathy The combined impact of new computing resources and techniques with an increasing avalanche of large datasets, is transforming many research areas and may l... A Al-Karawi,E Avar - 《Multimedia Tools...
The work was partially supported by the National Research Foundation of Ukraine in the framework of the grant 2020.01/0490 "Artificial Intelligence Platform for Distant Computer-Aided Detection (CADe) and Computer-Aided Diagnosis (CADx) of Human Diseases. Yuri Gordienko is NVIDIA Deep Learning Instit...
Efficient Low-Latency Dynamic Licensing for Deep Neural Network Deployment on Edge Devices Along with the rapid development in the field of artificial intelligence, especially deep learning, deep neural network applications are becoming more and more popular in reality. To be able to withstand the hea...