TI IDEP－01004嵌入应用深度学习推理参考设计

TI公司的TIDEP-01004是嵌入应用深度学习推理的参考设计,基于Sitara AM57x系列系统级芯片(SoC).参考设计表明了如何在C66x DSP核(AM57x SoC)和嵌入视频引擎(VEV)子系统上运行深度学习推理.深度学习是一种机器学习,训练计算机实现人类任务如区分图像,识别语音或进行时间序列预测. 深度学习是人工智能(AI)的基础.它的模型是基于深层人工神经网络,也称作深度神经网(DNN).在DNN内,有许久不同的神经网络结构如卷积神经网络(CNN)和循环神经网络(RNN),能够解决不同类型问题.CNN模型在解决计算机可视问题很有希望,非常适合于图像分类,物体检测和语义分割.参考设计TIDEP-01004主要用在自动分类设备,光学检测,可视计算机,代码阅读器,工业机器人,物流机器人,钞票计数器,ATM,病人监护,建筑物自动化,工业交通,航天,航空电子和国防.中电网为您整理如下详细资料,本文介绍了参考设计TIDEP-01004主要特性,框图, TI深度学习(TIDL)开发流程图以及AM574x Sitara™处理器主要特性,框图, AM574x工业开发套件电路图和材料清单.
This reference design demonstrates how to use TIDeep Learning (TIDL) on a Sitara AM57x System-on-Chip (SoC) to bring deep learning inference to anembedded application. This design shows how to rundeep learning inference on either C66x DSP cores(available in all AM57x SoCs) and Embedded VisionEngine (EVE) subsystems, which are treated as blackboxed deep learning accelerators on the AM5749SoC.
This reference design is applicable to any applicationthat is looking to bring deep learning inference into anembedded application.
Customers looking to quickly get started with a deeplearning network or to evaluate their own networksperformance on an AM57x device will find a step-by-stepguide on how to use TIDL available as part of TI’sfree AM57x Processor SDK.
Deep learning is a type of machine learning that trains a computer to perform human-like tasks, such asidentifying images, recognizing speech, or making predictions in time series. Instead of organizing data torun through predefined equations, deep learning sets up basic parameters about the data and trains thecomputer to learn on its own by recognizing patterns using many layers...