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Ai Solution

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  • FLEX-BX210-Q470

    Overview

    » Supported CPUs:

    Intel® Core™ i3-10320 3.8 GHz (up to 4.6 GHz, quad-core, 65W TDP)

    Intel® Core™ i5-10500TE 2.3 GHz (up to 3.7 GHz, 6-core, 35W TDP)

    Intel® Core™ i7-10700TE 2.0 GHz (up to 4.4 GHz, 8-core, 35W TDP)

    » Four hot-swappable HDD/SSD bays with RAID 0/1/5/10 support

    » Equipped with PCIe 3.0 x4 slots and PCIe 3.0 x8 slots

    » M.2 2280 PCIe Gen 3 x4 supporting NVMe

    » Support IEI Mustang accelerator cards

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  • Mustang-T100-T5

    Overview

    » 5 x Google Edge TPU ML accelerator

    » 20 TOPS peak performance (int8)

    » Host interface PCIe Gen2 x 4

    » Low-profile PCIe form factor

    » Support Multiple card

    » Approximate 15W

    » RoHS compliants

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  • PPC-F17B-BT  [ KC인증 ]

    Overview

    » Support IEI iRIS-2400 remote intelligent solution

    » Intel® Celeron® J1900 quad-core SoC

    » Robust IP65 aluminum front bezel

    » Aesthetic ultra-thin bezel for seamless panel mount installation

    » Projected capacitive multi-touch and resistive single touch options

    » Dual full-size PCIe Mini card expansion

    » 9V~36V DC wide range DC input

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  • PPC-F10B-BT  [ KC인증 ]

    Overview

    » 5.7”, 8” and 10.4” fanless industrial panel PC

    » 2.0 GHz Intel® Celeron® J1900 quad-core processor or 1.58 GHz Intel® Celeron® N2807 dual-core processor

    » Low power consumption DDR3L memory supported

    » IP 65 compliant front panel

    » 9 V~30 V wide DC input

    » mSATA SSD suppoted

    » Dual GbE for backup

    • » -10°C~50°C extended operating temperature
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  • Mustang-M2BM-MX2  [ SAMPLE ]

    Overview

    •Operating Systems
    Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit,Windows® 10 64bit
    •OpenVINO™ toolkit
    ◦Intel® Deep Learning Deployment Toolkit
    - Model Optimizer
    - Inference Engine
    ◦Optimized computer vision libraries
    ◦Intel® Media SDK
    •Current Supported Topologies: AlexNet, GoogleNetV1/V2, MobileNet SSD, MobileNetV1/V2, MTCNN, Squeezenet1.0/1.1, Tiny Yolo V1 & V2, Yolo V2, ResNet-18/50/101
    * For more topologies support information please refer to Intel® OpenVINO™ Toolkit official website.
    •High flexibility, Mustang-M2BM-MX2 develop on OpenVINO™ toolkit structure which allows trained data such as Caffe, TensorFlow, MXNet, and ONNX to execute on it after convert to optimized IR.
     

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  • Mustang-M2AE-MX1  [ SAMPLE ]

    Overview

    •Operating Systems
    Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit, Windows® 10 64bit
    •OpenVINO™ toolkit
    ◦Intel® Deep Learning Deployment Toolkit
    - Model Optimizer
    - Inference Engine
    ◦Optimized computer vision libraries
    ◦Intel® Media SDK

    •Current Supported Topologies: AlexNet, GoogleNetV1/V2, MobileNet SSD, MobileNetV1/V2, MTCNN, Squeezenet1.0/1.1, Tiny Yolo V1 & V2, Yolo V2, ResNet-18/50/101
    * For more topologies support information please refer to Intel® OpenVINO™ Toolkit official website.
    •High flexibility, Mustang-M2AE-MX1 develop on OpenVINO™ toolkit structure which allows trained data such as Caffe, TensorFlow, MXNet, and ONNX to execute on it after convert to optimized IR.

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  • Mustang-MPCIE-MX2  [ KC인증 ]

    Overview

    ● miniPCIe form factor (30 x 50 mm)
    ● 2 x Intel® Movidius™ Myriad™ X VPU MA2485
    ● Power efficiency ,approximate 7.5W
    ● Operating Temperature -20°C~60°C
    ● Powered by Intel’s OpenVINO™ toolkit
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  • Mustang-V100-MX4  [ KC인증 ]

    Overview

    •Operating Systems
    Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit , Windows® 10 64bit
    •OpenVINO™ toolkit
    ◦Intel® Deep Learning Deployment Toolkit
    - Model Optimizer
    - Inference Engine
    ◦Optimized computer vision libraries
    ◦Intel® Media SDK
    ◦Current Supported Topologies: AlexNet, GoogleNetV1/V2, MobileNet SSD, MobileNetV1/V2, MTCNN, Squeezenet1.0/1.1, Tiny Yolo V1 & V2, Yolo V2, ResNet-18/50/101
    * For more topologies support information please refer to Intel® OpenVINO™ Toolkit official website.
    ◦High flexibility, Mustang-V100-MX4 develop on OpenVINO™ toolkit structure which allows trained data such as Caffe, TensorFlow, MXNet, and ONNX to execute on it after convert to optimized IR.

     

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  • Mustang-V100-MX8  [ KC인증 ]  [ 단종 ]

    단종

    Overview

    •Operating Systems
    Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit, Windows 10 64bit.
    •OpenVINO™ Toolkit
    ◦Intel® Deep Learning Deployment Toolkit
    - Model Optimizer
    - Inference Engine
    ◦Optimized computer vision libraries
    ◦Intel® Media SDK
    ◦*OpenCL™ graphics drivers and runtimes.
    ◦Current Supported Topologies: AlexNet, GoogleNetV1/V2, MobileNet SSD, MobileNetV1/V2, MTCNN, Squeezenet1.0/1.1, Tiny Yolo V1 & V2, Yolo V2, ResNet-18/50/101
    - For more topologies support information please refer to Intel® OpenVINO™ Toolkit official website.

    •High flexibility, Mustang-V100-MX8 develop on OpenVINO™ toolkit structure which allows trained data such as Caffe, TensorFlow, and MXNet to execute on it after convert to optimized IR.
    *OpenCL™ is the trademark of Apple Inc. used by permission by Khronos

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  • Mustang-F100-A10  [ SAMPLE ]

    Overview

    •Operating Systems
    Ubuntu 16.04.3 LTS 64bit, CentOS 7.4 64bit (Support Windows 10 in the end of 2018 & more OS are coming soon)
    •OpenVINO™ toolkit

    ◦Intel® Deep Learning Deployment Toolkit

    - Model Optimizer
    - Inference Engine

    ◦Optimized computer vision libraries
    ◦Intel® Media SDK
    ◦*OpenCL™ graphics drivers and runtimes.
    ◦Current Supported Topologies: AlexNet, GoogleNet, Tiny Yolo, LeNet, SqueezeNet, VGG16, ResNet (more variants are coming soon)
    ◦Intel® FPGA Deep Learning Acceleration Suite

    •High flexibility, Mustang-F100-A10 develop on OpenVINO™ toolkit structure which allows trained data such as Caffe, TensorFlow, and MXNet to execute on it after convert to optimized IR.
    *OpenCL™ is the trademark of Apple Inc. used by permission by Khronos

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처음페이지 1 2 마지막페이지