Abstract:
Methods, systems, and devices for object detection are described. A device may receive an image, and detect, via a first stage of a cascade neural network, object recognition information over one or more angular orientations during a first pass. The device may determine, via a second stage of the cascade neural network, a confidence score associated with one or more of the candidate object in the image, the candidate bounding box associated with the candidate object in the image, or one or more object features of the candidate object in the image, or an orientation of the candidate object in the image, or a combination thereof. The device may identify, via a third stage of the cascade neural network, whether to detect the object recognition information during a second pass based on the confidence score satisfying a threshold.
Abstract:
An output driver for electrostatic discharge (ESD) protection includes a first pair of stacked metal oxide semiconductor field-effect transistor (MOS) devices coupled between a power terminal and a first differential output terminal. The output driver also includes a second pair of stacked MOS devices coupled between a second differential output terminal and a ground terminal.
Abstract:
An output driver for electrostatic discharge (ESD) protection includes a first pair of stacked metal oxide semiconductor field-effect transistor (MOS) devices coupled between a power terminal and a first differential output terminal. The output driver also includes a second pair of stacked MOS devices coupled between a second differential output terminal and a ground terminal.
Abstract:
Methods, systems, and devices for object detection are described. A device may receive an image, and detect, via a first stage of a cascade neural network, object recognition information over one or more angular orientations during a first pass. The device may determine, via a second stage of the cascade neural network, a confidence score associated with one or more of the candidate object in the image, the candidate bounding box associated with the candidate object in the image, or one or more object features of the candidate object in the image, or an orientation of the candidate object in the image, or a combination thereof. The device may identify, via a third stage of the cascade neural network, whether to detect the object recognition information during a second pass based on the confidence score satisfying a threshold.