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Survey: Request for customer feedback

Please feel free to add comments if you choose "other" for any of the following questions.

Survey: Request for customer feedback
  1. What Deep Learning Framework do you use?60 votes
    1. TensorFlow
      53.33%
    2. Caffe
      21.67%
    3. PyTorch
        5.00%
    4. Caffe2
        0.00%
    5. CNTK
        0.00%
    6. MXNet
        6.67%
    7. Chainer
        5.00%
    8. Other
        8.33%
  2. What use cases are you most interested in?60 votes
    1. Image Classification
      18.33%
    2. Object Detection
      36.67%
    3. Image Segmentation
      10.00%
    4. Audio Classification
        0.00%
    5. Natural Language Processing
        1.67%
    6. Deep Reinforcement Learning
        1.67%
    7. Chat Bot
        3.33%
    8. Stereo Depth
        0.00%
    9. Image Captioning
        0.00%
    10. SLaM
        1.67%
    11. Face Detection and Recognition
      20.00%
    12. Other
        6.67%
  3. What Networks do you commonly work with?60 votes
    1. MobileNet
      11.67%
    2. VGG
        5.00%
    3. Inception
      11.67%
    4. Inception-ResNet
        8.33%
    5. ResNet
        5.00%
    6. Faster RCNN
        5.00%
    7. SSD
      11.67%
    8. Yolo
      15.00%
    9. LSTM
        3.33%
    10. Other
      23.33%

Comments

  • 8 Comments sorted by Votes Date Added
  • An IMPORTANT user feedback is better documentation. The dev team please put sometime for that stuff. At the moment, NCS is great but poorly documented, and the Docs website is not properly constructed, like information is scattered and put anywhere possible. A neat and concise doc like those of Tensorflow or Keras or MxNet is greatly appreciated. Thanks!

  • Support of ONNX in the future would be nice.

  • What use cases are you most interested in? I think this question falls into what is the common
    terminology of the day issue.
    Yolo segments the image and classifys the objects in the image, that checks multiple boxes as does
    what Tensorflow calls this Tensorflow Object Detection API
    Is that what you are asking when you say Object detection? But isn't Tensorflows Object detection break down into segmenting
    then classifying the image segments of image giving the same result as YOLO?
    Or what do you call classifications?

  • is there any plan to support more types of layer?

  • @dvpo Thanks for the feedback. We really appreciate your input!

    @xhuan28 Yes we are planning to support more layers and features in future releases of the NCSDK.

  • @Tome_at_Intel , thanks for your prompt reply. That would be great you are planning to support more types of layer. From my perspective, I want ROIAlign and ROIPooling which are used in faster RCNN and FPN to be supported in future.
    Thanks.

  • Primary current network interest is SSD-MobleNet. I would especially like a tensorflow version to run on the NCS. In the near future my interest will probably include the mozilla Deep Speech model and face recognition.

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