edge intelligent systemsinferenceobject detectionresource constraintObject detection at the edge side is a common task in various environments. The deployment of convolutional neural networks in intelligent edge systems is very challenging because of the highly constrained mainmemory space. This study aims ...
However, compared to the cloud, edge servers typically have lower processing power and GPU memory, limiting the number of video streams that they can manage and analyze. Existing solutions for memory management, such as swapping models in and out of GPU, having a common model st...
【论文笔记】Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials,程序员大本营,技术文章内容聚合第一站。
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials Intro 回顾一下经典,文章是早期像素级分类做分割效果不好的情况下,利用条件随机场建模,解决细节分割问题的一篇文章,文章主要贡献是提出了Mean Fi
ultimately efficient solutions designed for edge and end-point inference, including the first generation of AI/ML hardware accelerator intellectual property (IP), the AndesAIRE™ AnDLA™ I350 (Andes Deep Learning Accelerator), and the neural network software tools and runtimes, the AndesAIRE™ ...
(AI) technologies, edge computing is emerging as a near-data source computing model. Due to the limited computing resources of edge devices, it is essential to measure and analyze the performance of neural network models to ensure efficient use of these resources during inference on edge devices...
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials阅读笔记 主要贡献·:为全连接CRF实现的一个高效近似推断随机算法,其成对边势被一组线性高斯核所定义。 目标:将图像中的每个像素按照预设的分类目录来贴标签,同时对多目标类进行识别和分割。一种比较常见的方法是最大后验估计。CRF势中包含...
学习笔记Galaxy: A Resource-Efficient Collaborative Edge AI System for In-situ Transformer Inference 本文是2024年IFOCOM的论文,主要解决的问题是如何更好的使用边缘设备进行协同transformer架构的推理。 Introduction 首先介绍了cloud-assisted方法的问题 边缘设备和远程云服务器间连接不稳定...
The privacy leakage surface covers the entire DL inference pipeline, where we mainly consider the privacy risks of the model intellectual property [24]. When employing edge-side DL inference, DNN models are stored locally on the edge server or user’s device, which presents new security challenge...
In this paper, we propose a practical solution to this problem that exploits deep learning on the edge. The developed system integrates an OpenMV microcontroller into a DJI Tello Micro Aerial Vehicle (MAV). The microcontroller hosts a set of machine learning-enabled inference tools that cooperate...