Abstract: The present disclosure provides devices, systems and methods for mapping of traffic boundaries.

Abstract: A neural network is configured to process image data captured by a vehicle-mounted camera. The neural network includes common processing layers (a trunk) and separate, parallelizable processing layers (branches). An object detection branch of the neural network is trained to detect objects that may be visible from the vehicle-mounted camera, such as cars, trucks, and traffic signs. A curve determination branch is trained to detect and parameterize salient curves, such as lane boundaries and road boundaries. The curve determination branch itself is configured with a trunk and branch architecture, having both common and separate processing layers. A first branch computes a likelihood that a curve is present in a given location of the image data and a second branch further localizes the curve within the given location if such a curve is present. Training of the different branches of the neural network may be decoupled.

Abstract: The present disclosure provides devices, systems and methods for a vehicular sensor system that detects and classifies objects, and further determining a vanishing point and aspect ratios, which enable detecting a misalignment of a lens focus and determining quality metrics; and calibrating the sensor system.

Abstract: A neural network is configured to process image data captured by a vehicle-mounted camera. The neural network includes common processing layers (a trunk) and separate, parallelizable processing layers (branches). An object detection branch of the neural network is trained to detect objects that may be visible from the vehicle-mounted camera, such as cars, trucks, and traffic signs. A curve determination branch is trained to detect and parameterize salient curves, such as lane boundaries and road boundaries. The curve determination branch itself is configured with a trunk and branch architecture, having both common and separate processing layers. A first branch computes a likelihood that a curve is present in a given location of the image data and a second branch further localizes the curve within the given location if such a curve is present. Training of the different branches of the neural network may be decoupled.

Abstract: A neural network is configured to process image data captured by a vehicle-mounted camera. The neural network includes common processing layers (a trunk) and separate, parallelizable processing layers (branches). An object detection branch of the neural network is trained to detect objects that may be visible from the vehicle-mounted camera, such as cars, trucks, and traffic signs. A curve determination branch is trained to detect and parameterize salient curves, such as lane boundaries and road boundaries. The curve determination branch itself is configured with a trunk and branch architecture, having both common and separate processing layers. A first branch computes a likelihood that a curve is present in a given location of the image data and a second branch further localizes the curve within the given location if such a curve is present. Training of the different branches of the neural network may be decoupled.

Abstract: The present disclosure provides devices, systems and methods for mapping of traffic boundaries.

Abstract: The present disclosure provides devices, systems and methods for mapping of traffic boundaries.

Abstract: The present disclosure provides devices, systems and methods for mapping of traffic boundaries.

Abstract: The present disclosure provides systems and methods for determining a curve.

Abstract: In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus for a neural network are provided. The neural network may be a multi-dimensional recurrent neural network. The multi-dimensional recurrent neural network may be trained via multi-dimensional backpropagation through time. The apparatus may receive a multi-dimensional input for the neural network. The apparatus may generate a multi-dimensional output for the neural network. At least one dimension of the multi-dimensional output may have variable length that is unrelated to dimensional lengths of the multi-dimensional input.

Abstract: The various technologies presented herein relate to various hybrid phononic-photonic waveguide structures that can exhibit nonlinear behavior associated with traveling-wave forward stimulated Brillouin scattering (forward-SBS). The various structures can simultaneously guide photons and phonons in a suspended membrane. By utilizing a suspended membrane, a substrate pathway can be eliminated for loss of phonons that suppresses SBS in conventional silicon-on-insulator (SOI) waveguides. Consequently, forward-SBS nonlinear susceptibilities are achievable at about 3000 times greater than achievable with a conventional waveguide system. Owing to the strong phonon-photon coupling achievable with the various embodiments, potential application for the various embodiments presented herein cover a range of radiofrequency (RF) and photonic signal processing applications. Further, the various embodiments presented herein are applicable to applications operating over a wide bandwidth, e.g. 100 MHz to 50 GHz or more.

Abstract: A radio-frequency photonic devices employs photon-phonon coupling for information transfer. The device includes a membrane in which a two-dimensionally periodic phononic crystal (PnC) structure is patterned. The device also includes at least a first optical waveguide embedded in the membrane. At least a first line-defect region interrupts the PnC structure. The first optical waveguide is embedded within the line-defect region.

Abstract: Methods and systems for stabilizing a resonant modulator include receiving pre-modulation and post-modulation portions of a carrier signal, determining the average power from these portions, comparing an average input power to the average output power, and operating a heater coupled to the modulator based on the comparison. One system includes a pair of input structures, one or more processing elements, a comparator, and a control element. The input structures are configured to extract pre-modulation and post-modulation portions of a carrier signal. The processing elements are configured to determine average powers from the extracted portions. The comparator is configured to compare the average input power and the average output power. The control element operates a heater coupled to the modulator based on the comparison.

Abstract: The various technologies presented herein relate to various hybrid phononic-photonic waveguide structures that can exhibit nonlinear behavior associated with traveling-wave forward stimulated Brillouin scattering (forward-SBS). The various structures can simultaneously guide photons and phonons in a suspended membrane. By utilizing a suspended membrane, a substrate pathway can be eliminated for loss of phonons that suppresses SBS in conventional silicon-on-insulator (SOI) waveguides. Consequently, forward-SBS nonlinear susceptibilities are achievable at about 3000 times greater than achievable with a conventional waveguide system. Owing to the strong phonon-photon coupling achievable with the various embodiments, potential application for the various embodiments presented herein cover a range of radiofrequency (RF) and photonic signal processing applications. Further, the various embodiments presented herein are applicable to applications operating over a wide bandwidth, e.g. 100 MHz to 50 GHz or more.

Abstract: The resonant frequency of an optical micro-resonator may be controlled by “locking” an operating frequency/wavelength of the resonator using CMOS compatible electronic components.