Abstract: An electronic package structure and a chip thereof are provided. The electronic package structure includes a supporting element, a chip, an internal bonding wire, and a plurality of external bonding wires. The supporting element has a chip arrangement portion. The chip has a first surface and a second surface opposite to the first surface. The chip is arranged on the chip arrangement portion with the second surface facing toward the supporting element. The chip includes a first common pad and an individual core pad that are disposed on the first surface. The internal bonding wire is connected between the first common pad and the individual core pad. The external bonding wires are connected between the chip and the supporting element, in which a first external bonding wire of the external bonding wires and the internal bonding wire are jointly connected to the first common pad.

Abstract: A device includes a conductive feature, a first dielectric layer, a via, an etch stop layer, a second dielectric layer, and a conductive line. The first dielectric layer is above the conductive feature. The via is in the first dielectric layer and above the conductive feature. The etch stop layer is above the first dielectric layer. A side surface of the etch stop layer is coterminous with a sidewall of the via. The second dielectric layer is above the etch stop layer. The conductive line is in the second dielectric layer and over the via. The conductive line is in contact with the side surface of the etch stop layer and a top surface of the etch stop layer.

Abstract: A method for determining deblur filter coefficients includes the following steps: generating an edge profile according to the data of a blurred image; estimating a blur kernel according to the edge profile, wherein the blur kernel indicates how an imaging process blurs original image data and thereby generates blurred image data; and determining coefficients of a deblur filter to make a process result of the deblur filter processing the blurred image data approach the original image data.

Abstract: A character recognition method includes the following operations: determining that the image of character to be identified corresponds to a matching character of several registered characters according to several vector distances to be identified between a vector of an image of character to be identified and several vectors of several registered character images of several registered characters, and storing a matching vector distance between the vector of the image of character to be identified and a vector of the matching character by a processor; and storing a data of the matching character according to the image of character to be identified when the matching vector distance is less than a vector distance threshold by the processor.

Abstract: An object detection model training apparatus, method and non-transitory computer readable storage medium thereof are provided. The apparatus performs a first object detection on a plurality of training images to generate a piece of first label information corresponding to each of the training images by a first teacher model. The apparatus trains a student model based on the training images and the first label information. The apparatus performs a second object detection on the training images to generate a piece of second label information corresponding to each of the training images by a second teacher model. The apparatus trains the student model based on the training images and the second label information.

Abstract: An echo cancelling system includes a data transmitter circuit and an echo canceller circuit. The data transmitter circuit is configured to receive a first transmitted signal. The first transmitted signal has a first sampling rate. The echo canceller circuit is configured to generate a second transmitted signal according to the first transmitted signal. The second transmitted signal has a second sampling rate. The second sampling rate is greater than the first sampling rate. The echo canceller circuit is further configured to generate an echo cancelling signal according to the second transmitted signal. The data transmitter circuit is further configured to generate an output signal according to a received signal and the echo cancelling signal.

Abstract: An electronic system including a display device, an image sensor, a face detection engine, an eye detection engine and an eye protection engine is provided. The image sensor captures an image. The face detection engine recognizes a user face in the image. The eye detection engine recognizes user eyes in the image. The eye protection engine turns off the display device when the user eyes are recognized in the image but the user face is not recognized in the image.

Abstract: There is provided a recognition system adaptable to a portable device or a wearable device. The recognition system senses a body heat using a thermal sensor, and performs functions such as the living body recognition, image denoising and body temperature prompting according to detected results.

Abstract: The present invention discloses a signal gain tuning circuit having adaptive mechanism. An amplifier receives an analog signal to generate a tuned analog signal to an ADC circuit to further generate a digital signal. A gain control capacitor array and the amplifier together determine a gain of the tuned analog signal. The control circuit receives an actual level of the digital signal to determine an offset of the digital signal and an estimated level to generate a tuning control signal. Each of coarse-tuning capacitors of a coarse-tuning capacitor array corresponds to a first tuning amount relative to a maximal gain. Each of fine-tuning capacitors of a fine-tuning capacitor array corresponds to a second tuning amount relative to the maximal gain. A tuning capacitor enabling combination of the coarse-tuning and fine-tuning capacitor arrays are determined according to the tuning control signal to tune the gain and decrease the offset.

Abstract: A method for training a deep learning network for face recognition includes: utilizing a face landmark detector to perform face alignment processing on at least one captured image, thereby outputting at least one aligned image; inputting the at least one aligned image to a teacher model to obtain a first output vector; inputting the at least one captured image a student model corresponding to the teacher module to obtain a second output vector; and adjusting parameter settings of the student model according to the first output vector and the second output vector.

Abstract: An emulation system traverses trace buffers to read data captured from a design under test (DUT). The emulation system receives a request to read at least a portion of DUT data. The emulation system reads a header of the latest sample of the DUT data, where header of each sample of the DUT data includes one or more pointers to a previously stored sample. The samples of the DUT data are partitioned into frames and sectors. The emulation system can identify samples of the DUT data using the pointers in the header of the samples and compare time stamps of the samples against a specified time stamp in the received request. After identifying a sample having the specified time stamp, the emulation system may read the sample for output to the user (e.g., reconstructing a waveform using the sample).

Abstract: Parameter calibration method for calibrating multiple parameters corresponding to multiple electronic components to be calibrated in a circuit, including steps: (A) turning off all of the electronic components to be calibrated and selecting a first electronic component from the electronic components to be calibrated as an electronic component being calibrated; (B) turning on the electronic component being calibrated and performing a calibration procedure on the electronic component being calibrated to determine a setting value of a parameter corresponding to the electronic component being calibrated; and (C) selecting a second electronic component from the electronic components to be calibrated as the electronic component being calibrated and performing step (B).

Abstract: A device may detect a semiconductor wafer to be transferred from a source wafer carrier to a target wafer carrier, and may cause a light source to illuminate the semiconductor wafer. The device may cause a camera to capture images of the semiconductor wafer after the light source illuminates the semiconductor wafer, and may perform image recognition of the images of the semiconductor wafer to determine whether an edge of the semiconductor wafer is damaged. The device may cause the semiconductor wafer to be provided to the source wafer carrier when the edge of the semiconductor wafer is determined to be damaged, and may cause the semiconductor wafer to be provided to the target wafer carrier when the edge of the semiconductor wafer is determined to be undamaged.

Abstract: A transistor includes a channel layer, a gate stack, and source/drain regions. The channel layer includes a graphene layer and hexagonal boron nitride (hBN) flakes dispersed in the graphene layer. Orientations of the hBN flakes are substantially aligned. The gate stack is over the channel layer. The source/drain regions are aside the gate stack.

Abstract: A semiconductor structure includes a semiconductor substrate, a plurality of stacked units, a conductive structure, a plurality of dielectrics, a first electrode strip, a second electrode strip, and a plurality of contact structures. The stacked units are stacked up over the semiconductor substrate, and comprises a first passivation layer, a second passivation layer and a channel layer sandwiched between the first passivation layer and the second passivation layer. The conductive structure is disposed on the semiconductor substrate and wrapping around the stacked units. The dielectrics are surrounding the stacked units and separating the stacked units from the conductive structure. The first electrode strip and the second electrode strip are located on two opposing sides of the conductive structure. The contact structures are connecting the channel layer of each of the stacked units to the first electrode strip and the second electrode strip.

Abstract: A portable electronic device to be used as a keyless device of a vehicle includes a controlling circuit which includes a physiological feature detection module and a processing circuit. The physiological feature detection module is used for detecting a physiological feature of a person. The processing circuit is coupled to the physiological feature detection module and used for determining whether the person is an authorized user of the vehicle according to the detected physiological feature of the person, and for opening a car door of the vehicle or starting the vehicle when the person is identified by the processing circuit as the authorized user.

Abstract: A method of data augmentation is provided. The method includes the following operations: selecting an original image from an original dataset including label data configured to indicate a labeled area of the original image; selecting at least part of content, located in the labeled area, of the original image as a first target image; generating a first sample image according to the first target image, in which the first sample image includes the first target image and a first border pattern different from the first target image, and the content, located in the labeled area, of the original image is free from including at least part of the first border pattern; and incorporating the first sample image into a sample dataset, in which the sample dataset is configured to be inputted to a machine learning model.

Abstract: There is provided a human falling detection system including an image sensor, a thermal sensor and a microphone. The image sensor captures an image frame that is used to identify a face and a height-width ratio of a human image. The thermal sensor is used as a filter for filtering out a living body and captures a thermal image that is used to identify a height-width ratio of a human thermal image. The microphone records a time stamp of an abrupt sound appearing.

Abstract: An embodiment is method including forming a first die package over a carrier substrate, the first die package comprising a first die, forming a first redistribution layer over and coupled to the first die, the first redistribution layer including one or more metal layers disposed in one or more dielectric layers, adhering a second die over the redistribution layer, laminating a first dielectric material over the second die and the first redistribution layer, forming first vias through the first dielectric material to the second die and forming second vias through the first dielectric material to the first redistribution layer, and forming a second redistribution layer over the first dielectric material and over and coupled to the first vias and the second vias.

Abstract: A pixel value calibration method includes: obtaining input image data generated by pixels, the input image data including a first group of pixel values in a first color plane and a second group of pixel values in a second color plane, generated by a first portion and a second portion of the pixels respectively; determining a difference function associated with filter response values and target values, the filter response values being generated by utilizing characteristic filter coefficients to filter first and second estimated pixel values of estimated pixel data in the first and second color planes, respectively; determining a set of calibration filter coefficients by calculating a solution of the estimated pixel data, the solution resulting in a minimum value of the difference function; and filtering the input image data, by a filter circuit using the set of calibration filter coefficients, to calibrate the first group of pixel values.