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  • Processors

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TPU Processors
  • BM1684
    BM1684

    TPU processor, 17.6TOPS, 32 channels of full HD video decoding

AI Vision Processors
  • CV1838
    CV1838

    4K Super Definition AI vision processor

  • CV1835
    CV1835

    5M high-performance AI vision processor

  • CV1821/CV1822
    CV1821/CV1822

    5M slightly intelligent AI vision processor

  • CV7357/CV7327
    CV7357/CV7327

    2K+2M smart car vision processor

Intelligent Server
  • SG6-10-B22 Intelligent Server
    SG6-10-B22 Intelligent Server

    AI server, 528TOPS, 960 channels of full HD video decoding

  • SG6-06-A22 Intelligent Server
    SG6-06-A22 Intelligent Server

    AI server, 316.8TOPS, 576 channels of full HD video decoding

Micro Server
  • AI Micro Server SE6-192
    AI Micro Server SE6-192

    AI micro server, 211.2TOPS, 456 channels of full HD video decoding

  • AI Micro Server SE5-16
    AI Micro Server SE5-16

    AI micro server, 17.6TOPS, 32 channels of full HD video decoding

  • AI Micro Server SE5-8
    AI Micro Server SE5-8

    AI micro server, 10.6TOPS, 8 channels of full HD video decoding

Smart Card
  • AI Accelerator Card SC5+
    AI Accelerator Card SC5+

    AI inference card, 52.8TOPS, 96 channels of full HD video decoding

  • AI Accelerator Card SC5H
    AI Accelerator Card SC5H

    AI inference card, 17.6TOPS, 32 channels of full HD video decoding

Smart Computing module
  • AI Computing Module SM5 Mini
    AI Computing Module SM5 Mini

    AI edge inference module, 17.6TOPS, 32 channels of full HD video decoding

  • AI Computing Module SM5
    AI Computing Module SM5

    AI edge inference module, 17.6TOPS, 32 channels of full HD video decoding

  • AI Developer Product Portfolio
    AI Developer Product Portfolio

    AI Developer Product Portfolio

算丰学院 / 少林派开发板实战课 / 少林派开发板刷机升级流程

算丰学院-少林派开发板实战课-少林派开发板刷机升级流程

课件资料

少林派开发板刷机升级指南 少林派开发板刷机升级指南文档

课程章节 (19节课)

1_ 产品介绍
1.1 少林派开发板介绍
2_ 开发指南
2.1 少林派HDMI连接显示Ubuntu桌面端
3_ 环境搭建
3.1 少林派开发板刷机升级流程
4_ AI实战
4.1 基于少林派及LeNet5的手写数字识别
4.2 基于少林派及ResNet的猫狗分类
4.3 基于少林派及YOLOv5的目标检测
4.4 基于少林派的YOLO3D实战项目
4.5 基于少林派及ICNet神经网络实现道路场景分割
4.6 基于少林派及LSTM的股票预测
4.7 基于少林派及ReconNet的图像重建
4.8 基于少林派及Mask R-CNN神经网络实现实例分割
4.9 基于少林派及RetinaFace实现人脸识别
4.10 基于少林派及CenterNet实现图像分割
4.11 基于少林派及LPRNet的目标检测算法移植与测试
4.12 基于少林派及PP-OCRv2实现文本识别
4.13 基于少林派及Yolact实现目标跟踪
4.14 基于少林派及FALSR超分辨率图像模型测试
4.15 基于少林派及HRNet的姿态识别
4.16 基于少林派及MiDas的深度估计算法
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