Abstract: A memory device includes a plurality of word lines (WLs). The memory device includes a plurality of drivers that are each configured to control a corresponding one of the plurality of WLs and each comprise a first transistor having a first conductive type and a second transistor having a second conductive type. The first transistor of a first one of the drivers is formed in a first well of a substrate, and the second transistor of the first driver is formed in a second well of the substrate. The first well is spaced apart from the second well.

Abstract: A method for detecting three-dimensional (3D) objects in relation to autonomous driving is applied in an electronic device. The device obtains detection images and depth images, =inputs the detection images into a trained object detection model to determine categories of objects in the detection images and two-dimensional (2D) bounding boxes of the objects. The device determines object models of the objects and 3D bounding boxes of the object models according to the object categories, and calculates point cloud data of the objects selected and distances from the depth camera to the object models. The device determines angles of rotation of the object models of the objects according to the object models of the objects and the point cloud data, and can determine respective positions of the objects in 3D space according to the distance from the depth camera to the object models, the rotation angles, and the 3D bounding boxes.

Abstract: A method for detecting three-dimensional (3D) objects in roadway is applied in an electronic device. The device inputs training images into a semantic segmentation model, and performs convolution operations and pooling operations on the training images and obtains feature maps. The electronic device performs up-sampling operations on the feature maps to obtain first images, classifies pixels on the first images, calculates and optimizes a classification loss and obtains a trained semantic segmentation model. The device inputs the detection images into the trained semantic segmentation model, determines object models of the objects, point cloud data and distances from the depth camera to the object models, determines rotation angles of the object models according to the point cloud data and the object models, and determines positions of the object models in 3D space according to the distances, the rotation angles, and positions of the objects.

Abstract: Disclosed herein are related to a device for performing neuromorphic computing. In one aspect, a device includes a back end of line layer including a three-dimensional memory array. The three-dimensional memory array may include a plurality of memory cells to store a plurality sets of weight values of a neural network model. In one aspect, the device includes a front end of line layer including a controller. The controller may apply one or more input voltages corresponding to an input to the neural network model to the three-dimensional memory array, and receive one or more output voltages from the three-dimensional memory array to perform computations of the neural network model.

Abstract: An image recognition method applied to an electronic device is provided. The method includes constructing a first semantic segmentation network. In response that an initial labeled result of one of a plurality of initial labeled images does not match a preset labeled result, a target image corresponding to the one of the plurality of initial labeled images and a target labeled result of the target image are obtained. A second semantic segmentation network is obtained by training the first semantic segmentation network based on a plurality of the target images and the target labeled result of each target image, and a labeled result of an image to be recognized is obtained by inputting the image to be recognized into the second semantic segmentation network.

Abstract: A method for detection of three-dimensional (3D) objects on or around a roadway by machine learning, applied in an electronic device, obtains images of road, inputs the images into a trained object detection model, and determines categories of objects in the images, two-dimensional (2D) bounding boxes of the objects, and parallax (rotation)angles of the objects. The electronic device determines object models and 3D bounding boxes of the object models and determines distance from the camera to the object models according to size of the 2D bounding boxes, image information of the detection images, and focal length of the camera. The positions of the object models in a 3D space can be determined according to the rotation angles, the distance, and the 3D bounding boxes, and the positions of the object models are taken as the position of the objects in the 3D space.

Abstract: One or more components (e.g., devices) and/or component ensembles coupled to a local network utilize updatable software and/or firmware to perform, The component(s) (e.g., and ensembles thereof) can be updated using a scheme that enables recognition of the component(s) among a plurality of components, recognize the respective firmware and/or software versions, and targets relevant update(s) to component(s) requiring update.

Abstract: The present disclosure provides an etching solution, including an ionic strength enhancer having an ionic strength greater than 10?3 M in the etching solution, wherein the ionic strength enhancer includes Li+, Na+, K+, Mg2+, Ca2+, N(CH3)+, or N(C2H5)4+, a solvent, and an etchant.

Abstract: Surgical teaching auxiliary system using virtual reality and method thereof are disclosed. In the Surgical teaching auxiliary system, virtual-reality surgical environment is created through three-dimensional reconstruction based on a two-dimensional surgical image, and an operation step, a time point of using instrument and a reference message are preset in advance; when a surgical training is performed in the virtual-reality surgical environment, a surgical operation behavior is continuously detected; when the surgical operation behavior abnormally interrupted or delayed is detected, an auxiliary support and guidance are triggered based on a progress of the surgical training, thereby achieving the technical effect of greatly improving the effectiveness of surgical learning in the virtual reality.

Abstract: Apparatus and methods are disclosed for using machine learning models with private and public domains. Operations can be applied to transform input to a machine learning model in a private domain that is kept secret or otherwise made unavailable to third parties. In one example of the disclosed technology, a method includes applying a private transform to produce transformed input, providing the transformed input to a machine learning model that was trained using a training set modified by the private transform, and generating inferences with the machine learning model using the transformed input. Examples of suitable transforms that can be employed include matrix multiplication, time or spatial domain to frequency domains, and partitioning a neural network model such that an input and at least one hidden layer form part of the private domain, while the remaining layers form part of the public domain.

Abstract: A surgical decision support system based on augmented reality (AR) and a method thereof are disclosed. In the surgical decision support system, a surgeon can create an optimal surgical operation before a surgical operation; during a surgical operation, the optimal surgical operation can be demonstrated through augmented reality, a current surgical operation is detected and compared with the optimal surgical operation, a difference message is displayed to provide a surgical decision support when a comparison difference exceeds a tolerable range. Therefore, the technical effect of improving operation efficiency and success rate can be achieved.

Abstract: Implementations of the subject matter described herein provide a solution for rate control based on reinforcement learning. In this solution, an encoding state of a video encoder is determined, the encoding state being associated with encoding of a first video unit by the video encoder. An encoding parameter associated with rate control in the video encoder is determined by a reinforcement learning model and based on the encoding state of the video encoder. A second video unit different from the first video unit is encoded based on the encoding parameter. In this way, it is possible to achieve a better quality of experience (QOE) for real time communication with computation overhead being reduced.

Abstract: The present disclosure provides an etching solution, including an ionic strength enhancer having an ionic strength greater than 10?3 M in the etching solution, wherein the ionic strength enhancer includes Li+, Na+, K+, Mg2+, Ca2+, N(CH3)+, or N(C2H5)4+, a solvent, and an etchant.

Abstract: Apparatus and methods are disclosed for using machine learning models with private and public domains. Operations can be applied to transform input to a machine learning model in a private domain that is kept secret or otherwise made unavailable to third parties. In one example of the disclosed technology, a method includes applying a private transform to produce transformed input, providing the transformed input to a machine learning model that was trained using a training set modified by the private transform, and generating inferences with the machine learning model using the transformed input. Examples of suitable transforms that can be employed include matrix multiplication, time or spatial domain to frequency domains, and partitioning a neural network model such that an input and at least one hidden layer form part of the private domain, while the remaining layers form part of the public domain.

Abstract: A memory device includes a first layer, wherein the first layer includes a first memory array, a first row decoder circuit, and a first column sensing circuit. The memory device includes a second layer disposed with respect to the first layer in a vertical direction. The second layer includes a first peripheral circuit operatively coupled to the first memory array, the first row decoder circuit, and the first column sensing circuit. The memory device includes a plurality of interconnect structures extending along the vertical direction. At least a first one of the plurality of interconnect structures operatively couples the second layer to the first layer.

Abstract: A processor is provided with a register file comprising a plurality of vector registers, and an execution core coupled to the register file, where the execution core is configured to execute a set of checksum instructions with a first checksum instruction to specify a first vector operand, a second vector operand, and a result vector operand, where the first vector operand is in a first vector register of the plurality of vector registers, the second vector operand is in a second register of the plurality of vector registers, and the result vector operand is to be written to a third vector register of the plurality of vector registers, and to execute the first checksum instruction, the execution core is configured to accumulate bytes from the first vector operand and the second vector operand into a first portion of the result vector operand and add the accumulated bytes from the first vector operand and the second vector operand to a second portion of the result vector operand to generate the second portion

Abstract: An antenna structure applied in a wearable device includes a ceramic layer, a plastic layer, a radiating portion, a feed portion; and a connecting portion. The ceramic layer includes a first surface and a second surface corresponding to each other. The plastic layer is connected to the second surface. The radiating portion is a predetermined metal pattern and arranged in the first surface. The connecting portion passes through the plastic layer and is electrically connected to the feed portion. The feed portion feeds an electrical current to the radiating portion to generate radiation signals in at least one radiation frequency band. A wearable device having the antenna structure is also provided.

Abstract: An antenna structure applied in a wearable device includes a first radiating portion, a ceramic layer, a plastic layer, and a feed portion. The first radiating portion is a metal structure. The ceramic layer covers and contacts the first radiating portion. The first radiating portion is arranged between the ceramic layer and the plastic layer. The feed portion passes through the plastic layer and feeds an electric current into the first radiating portion, the first radiating portion and the ceramic layer cooperatively generate radiation signals in at least one radiation frequency band. A wearable device having the antenna structure is also provided.

Abstract: A semiconductor device includes a transistor that is disposed on a substrate. The transistor includes a gate electrode located over the substrate, a gate dielectric disposed on the gate electrode, a channel layer disposed on the gate dielectric, a first source/drain contact disposed on the channel layer and located on a side of the channel layer that is opposite to the substrate, and a second source/drain contact disposed on the channel layer and located on a side of the channel layer that faces the substrate. One of the gate dielectric and the channel layer at least partially surrounds the other one of the gate dielectric and the channel layer. A region of the channel layer between the first source/drain contact and the second source/drain contact is elongated in a direction perpendicular to the substrate.

Abstract: A method and apparatus for determining jitter, a storage medium and an electronic device are disclosed. The method for determining jitter includes: determining a plurality of measurement time points for an output signal from an integrated circuit (IC); identifying one or more jitter points from the plurality of measurement time points by comparing the output signal with a predetermined signal at the plurality of measurement time points; and determining a jitter of the output signal of the IC based on the one or more jitter points. The jitter of the output signal of an IC chip can be determined without relying on any other additional equipment.