Abstract: Systems and techniques are described herein for processing data (e.g., image data) using convolution as a transformer (CAT) operations. The method includes receiving, at a convolution engine of a machine learning system, a first set of features, the first set of features being associated with an image and having a three-dimensional shape, applying, via the convolution engine, a depth-wise separable convolutional filter to the first set of features to generate a first output, applying, via the convolution engine, a pointwise convolutional filter to the first output to generate a second output based on global information from a spatial dimension and a channel dimension associated with the image, modifying the second output to the three-dimensional shape to generate a second set of features and combining the first set of features and the second set of features to generate an output set of features.

Abstract: Systems and techniques are described herein for modifying the scale and/or position of objects in images. For instance, a system can obtain a two-dimensional (2D) input image from a camera and a three-dimensional (3D) representation of the 2D input image. The system can further determine a first portion of the 3D representation of the 2D input image corresponding to a target object in the 2D input image. The system can adjust a pose of the first portion of the 3D representation of the 2D input image corresponding to the target object. The system can further generate a 2D output image having a modified version of the target object based on the adjusted pose of the first portion of the 3D representation of the 2D input image corresponding to the target object to be output on a display.

Abstract: Methods, systems, and apparatuses for image segmentation are provided. For example, a computing device may obtain an image, and may apply a process to the image to generate input image feature data and input image segmentation data. Further, the computing device may obtain reference image feature data and reference image classification data for a plurality of reference images. The computing device may generate reference image segmentation data based on the reference image feature data, the reference image classification data, and the input image feature data. The computing device may further blend the input image segmentation data and the reference image segmentation data to generate blended image segmentation data. The computing device may store the blended image segmentation data within a data repository. In some examples, the computing device provides the blended image segmentation data for display.

Abstract: The present disclosure provides a multi-state one-time programmable (MSOTP) memory circuit including a memory cell and a programming voltage driving circuit. The memory cell includes a MOS storage transistor, a first MOS access transistor and a second MOS access transistor electrically connected to store two bits of data. When the memory cell is in a writing state, the programming voltage driving circuit outputs a writing control potential to the gate of the MOS storage transistor, and when the memory cell is in a reading state, the programming voltage driving circuit outputs a reading control potential to the gate of the MOS storage transistor.

Abstract: Systems and techniques are described for processing image data to generate an image with a synthetic depth of field (DoF). An imaging system receives first image data of a scene captured by a first image sensor. The imaging system receives second image data of the scene captured by a second image sensor. The first image sensor is offset from the second image sensor by an offset distance. The imaging system generates, using at least the first image data and the second image data as inputs to one or more trained machine learning systems, an image having a synthetic depth of field corresponding to a simulated aperture size. The simulated aperture size is associated with the offset distance. The imaging system outputs the image.

Abstract: Systems and techniques are described herein for modifying the scale and/or position of objects in images. For instance, a system can obtain a two-dimensional (2D) input image from a camera and a three-dimensional (3D) representation of the 2D input image. The system can further determine a first portion of the 3D representation of the 2D input image corresponding to a target object in the 2D input image. The system can adjust a pose of the first portion of the 3D representation of the 2D input image corresponding to the target object. The system can further generate a 2D output image having a modified version of the target object based on the adjusted pose of the first portion of the 3D representation of the 2D input image corresponding to the target object to be output on a display.

Abstract: Systems and techniques are described herein for modifying the scale and/or position of objects in images. For instance, a system can obtain a two-dimensional (2D) input image from a camera and a three-dimensional (3D) representation of the 2D input image. The system can further determine a first portion of the 3D representation of the 2D input image corresponding to a target object in the 2D input image. The system can adjust a pose of the first portion of the 3D representation of the 2D input image corresponding to the target object. The system can further generate a 2D output image having a modified version of the target object based on the adjusted pose of the first portion of the 3D representation of the 2D input image corresponding to the target object to be output on a display.

Abstract: Systems and techniques are described for processing image data to generate an image with a synthetic depth of field (DoF). An imaging system receives first image data of a scene captured by a first image sensor. The imaging system receives second image data of the scene captured by a second image sensor. The first image sensor is offset from the second image sensor by an offset distance. The imaging system generates, using at least the first image data and the second image data as inputs to one or more trained machine learning systems, an image having a synthetic depth of field corresponding to a simulated aperture size. The simulated aperture size is associated with the offset distance. The imaging system outputs the image.

Abstract: A handheld device and a frequency tracking method thereof are provided. The handheld device comprises an oscillator, a radio frequency (RF) chip, a modem module, a first thermal sensor and a thermal module. The oscillator generates an oscillation signal with an oscillation frequency. The RF chip is electrically connected to the oscillator and configured to receive a paging signal from a paging channel and an RF signal from a non-regular channel based on the oscillation signal. The modem module is electrically connected to the RF chip. The first thermal sensor disposed close to the oscillator measures a heat source temperature. The thermal module electrically connected to the modem module and the first thermal sensor enables the modem module to execute a frequency compensation process by using the RF signal of both the paging signal and the RF signal according to the heat source temperature.

Abstract: A handheld device and a frequency tracking method thereof are provided. The handheld device comprises an oscillator, a radio frequency (RF) chip, a modem module, a first thermal sensor and a thermal module. The oscillator generates an oscillation signal with an oscillation frequency. The RF chip is electrically connected to the oscillator and configured to receive a paging signal from a paging channel and an RF signal from a non-regular channel based on the oscillation signal. The modem module is electrically connected to the RF chip. The first thermal sensor disposed close to the oscillator measures a heat source temperature. The thermal module electrically connected to the modem module and the first thermal sensor enables the modem module to execute a frequency compensation process by using the RF signal of both the paging signal and the RF signal according to the heat source temperature.

Abstract: A surrounding cell monitoring method is applied in a mobile terminal wirelessly communicating with a first cell through a first target channel. The surrounding cell monitoring method includes the steps of: determining whether adjacent channel interference (ACI) of the target channel exists; determining whether a first power level of the adjacent channel is greater than a second power level of the target channel by a threshold difference when the ACI exists, when the ACI does exist; determining whether an adjacent BSIC of the adjacent channel can be decoded when the first power level is greater than the second power level by the threshold difference; and skipping an operation of decoding a target BSIC of the target channel when the adjacent BSIC of the adjacent channel can be decoded successfully.

Abstract: A surrounding cell monitoring method is applied in a mobile terminal wirelessly communicating with a first cell through a first target channel. The surrounding cell monitoring method includes the steps of: determining whether adjacent channel interference (ACI) of the target channel exists; determining whether a first power level of the adjacent channel is greater than a second power level of the target channel by a threshold difference when the ACI exists, when the ACI does exist; determining whether an adjacent BSIC of the adjacent channel can be decoded when the first power level is greater than the second power level by the threshold difference; and skipping an operation of decoding a target BSIC of the target channel when the adjacent BSIC of the adjacent channel can be decoded successfully.

Abstract: A computer motherboard with a Basic Input Output System (BIOS) is characterized by built-in BIOS fresh. The BIOS includes a first means and a second means. The first and second means are code internally provided in the BIOS and executable by a CPU of the computer motherboard in an execution environment preset by the BIOS. The first means selects a BIOS update file stored in a storage device. The second means enables the BIOS update file to be refreshed in a BIOS memory. After the computer motherboard enters a BIOS setup utility, a user selects an option of execution of the first or second means to let BIOS fresh takes place without using an operating system.