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Would it be able to detect textual regions in an image as it depics kite/persons in the example image?
Earlier quoted context omitted.
Mobile focused version of tensorflow.
Lol. Parallel data computations across resource (including battery) constrained devices? Good news, the owner of the device is now the product. The device is also the product. Can't wait.
Their repository is pretty neat! It includes three state-of-the-art architectures in object detection: Faster-RCNN, RFCN, and SSD. It is missing YOLO [1][2], though, which shares some similarities with SSD. Another detector is the recently released Mask-RCNN [3], which of course wouldn't be possible to be included in this publication as we can't travel through time yet. [1]: https://arxiv.org/abs/1506.02640 [2]: http…
In practice Faster R-CNN worked better for me than YOLOv2 as it, in contrast to what is reported in the paper, had a higher recall for the detect task I used it for.
Their repository is pretty neat! It includes three state-of-the-art architectures in object detection: Faster-RCNN, RFCN, and SSD. It is missing YOLO [1][2], though, which shares some similarities with SSD. Another detector is the recently released Mask-RCNN [3], which of course wouldn't be possible to be included in this publication as we can't travel through time yet. [1]: https://arxiv.org/abs/1506.02640 [2]: http…
There are already newer versions, Yolov2 and DSSD. See http://github.com/sbrugman/deep-learning-papers In practice Faster R-CNN worked better for me than YOLOv2 as it, in contrast to what is reported in the paper, had a higher recall for the detect task I used it for.
What's the hype here. It's a curated model zoo, or?
Earlier quoted context omitted.
Mobile focused version of tensorflow.
Lol. Parallel data computations across resource (including battery) constrained devices? Good news, the owner of the device is now the product. The device is also the product. Can't wait.
E.g. https://www.qualcomm.com/news/onq/2017/01/09/tensorflow-mach...
What's the hype here. It's a curated model zoo, or?
The researchers have created a framework for object detection such that one can easily experiment with using different feature extraction networks, separated from the "meta-architecture" such as Faster R-CNN, R-FCN, or SSD, used to handle the object detection task. They compare many models using this framework, described in https://arxiv.org/abs/1611.10012 - and they were able to construct the winning entry of the CO…