Abstract: An in-plane magnetized spin-orbit magnetic device is provided. The in-plane magnetized spin-orbit magnetic device includes a heavy metal layer, an upper electrode and a magnetic tunnel junction. The magnetic tunnel junction is disposed between the heavy metal layer and the upper electrode. The magnetic tunnel junction includes a free layer and a pinned layer. The free layer is disposed on the heavy metal layer, and the free layer has a first film plane area. The pinned layer is disposed on the free layer, and the pinned layer has a second film plane area. There is a preset angle between a long axis direction of a film plane shape of the free layer and a long axis direction of a film plane shape of the pinned layer, and the first film plane area is larger than the second film plane area.

Abstract: A non-transitory computer-readable medium of a device that stores computer-executable instructions is provided. When the instructions are executed by the device, the instructions cause the device to: determine a line index of a block unit determined from an image frame in the bitstream for selecting one of reference lines; compare the line index with a first predefined value to determine whether a mode flag is included in the bitstream; determine a mode index in the bitstream for directly selecting a prediction mode from a most probable mode (MPM) list when the mode flag is not included in the bitstream; compare the mode flag to a second predefined value when the mode flag is included in the bitstream to determine whether the prediction mode is selected from the MPM list based on the mode index; and reconstruct the block unit based on the selected reference line and the prediction mode.

Abstract: Machine learning is used to train a network to estimate a three-dimensional (3D) body surface and body regions of a patient from surface images of the patient. The estimated 3D body surface of the patient is used to determine an isocenter of the patient. The estimated body regions are used to generate heatmaps representing visible body region boundaries and unseen body region boundaries of the patient. The estimation of 3D body surfaces, the determined patient isocenter, and the estimated body region boundaries may assist in planning a medical scan, including automatic patient positioning.

Abstract: A device, structure, and method are provided whereby an insert layer is utilized to provide additional support for weaker and softer dielectric layer. The insert layer may be applied between two weaker dielectric layers or the insert layer may be used with a single layer of dielectric material. Once formed, trenches and vias are formed within the composite layers, and the insert layer will help to provide support that will limit or eliminate undesired bending or other structural motions that could hamper subsequent process steps, such as filling the trenches and vias with conductive material.

Abstract: A method of encoding or decoding video data includes constructing a list of chroma intra-prediction modes for a chroma block of a current block of the video data, wherein constructing includes adding intra-prediction modes of a first group to the list of chroma intra-prediction modes, the first group comprising two or more intra-prediction modes derived from intra-prediction modes of two or more co-located luma blocks of the current block that are co-located with the chroma block; determining an intra-prediction mode for the chroma block from the list of chroma intra-prediction modes; and encoding or decoding the chroma block based on the intra-prediction mode.

Abstract: A device for decoding video data includes a memory configured to store video data; and one or more processors implemented in circuitry and configured to: determine that a boundary block of a picture of the video data is bi-directional inter-predicted using a first motion vector and a second motion vector, the boundary block having an edge that touches an edge of the picture; decode the picture, including decoding the boundary block; form a first intermediate padding block using the first motion vector; form a second intermediate padding block using the second motion vector; form a padding block using the first intermediate padding block and the second intermediate padding block; and assign padding values of the padding block to a padding region of the picture neighboring the boundary block on an opposite side of the edge of the picture.

Abstract: An encoding, a decoding method, a system for encoding and decoding, an encoder, and a decoder are provided. The encoding method includes the following. In a palette mode, if colors of pixels of a coding unit block are all represented by one or more major colors of the coding unit block, a flag is set as a first state value, and if the color of at least one pixel of the coding unit block is not represented by the one or more major colors of the coding unit block, the flag is set as a second state value. The encoding method further includes establishing a palette table corresponding to the coding unit block according to a state value of the flag and the one or more major colors.

Abstract: A device, structure, and method are provided whereby an insert layer is utilized to provide additional support for weaker and softer dielectric layer. The insert layer may be applied between two weaker dielectric layers or the insert layer may be used with a single layer of dielectric material. Once formed, trenches and vias are formed within the composite layers, and the insert layer will help to provide support that will limit or eliminate undesired bending or other structural motions that could hamper subsequent process steps, such as filling the trenches and vias with conductive material.

Abstract: A method of encoding video data by an electronic device is provided. A block unit is determined from an image frame according to the video data. A line index is encoded in a bitstream based on a selected reference line of the block unit and is compared with a first predefined value to determine whether to encode a mode flag in the bitstream. A mode index is directly encoded in the bitstream for indicating a prediction mode of the block unit from a most probable mode (MPM) list of the block unit when the mode flag is not encoded. The mode flag is compared to a second predefined value for encoding the mode index when the mode flag is encoded in the bitstream to indicate whether the prediction mode is selected from the MPM list. The block unit is predicted based on the selected reference line and the prediction mode.

Abstract: A method of characterizing a serum or plasma portion of a specimen in a specimen container includes capturing a plurality of images of the specimen container from multiple viewpoints, stacking the multiple viewpoint images along a channel dimension into a single stacked input, and processing the stacked input with a single deep convolutional neural network (SDNN). The SDNN includes a segmentation convolutional neural network that receives the stacked input and outputs multiple label maps simultaneously. The SDNN also includes a classification convolutional neural network that processes the multiple label maps and outputs an HILN determination (Hemolysis, Icterus, and/or Lipemia, or Normal) of the serum or plasma portion of the specimen. Quality check modules and testing apparatus configured to carry out the method are also described, as are other aspects.

Abstract: A device for decoding video data can be configured to determine that a block is coded in an overlapped block motion compensation (OBMC) mode; determine a first prediction block for the block using a first motion vector for the block; determine a second prediction block for the block using a second motion vector, wherein the second motion is a motion vector of a neighboring block of the block; select an OBMC blending process from a plurality of available OBMC blending processes; blend the first prediction block and the second prediction block using the selected OBMC blending process to determine a blended block; and reconstruct the block using the blended block.

Abstract: A video coder is configured to determine a reference block of a reference picture for prediction of a current block of a current picture using motion information and to generate a set of reference samples for the current block of the current picture. To generate the set of reference samples, the video coder is configured to perform reference sample clipping on the reference block of the reference picture based on a size of the reference picture. The video coder is further configured to generate a prediction block for the current block of the current picture based on the set of reference samples.

Abstract: Machine learning is used to train a network to estimate a three-dimensional (3D) body surface and body regions of a patient from surface images of the patient. The estimated 3D body surface of the patient is used to determine an isocenter of the patient. The estimated body regions are used to generate heatmaps representing visible body region boundaries and unseen body region boundaries of the patient. The estimation of 3D body surfaces, the determined patient isocenter, and the estimated body region boundaries may assist in planning a medical scan, including automatic patient positioning.

Abstract: Patient biographic data may be estimated by receiving patient image data, applying the patient image data to a machine learned model, the machine learned model trained on second patient data and trained to map the second patient data to associated biographic data using machine learned features, generating the patient biographic data based on the applying and the machine learned features, and outputting the patient biographic data. The patient biographic data may include a patient weight, a patient height, a patient gender, and a patient age.

Abstract: A video decoder obtains a first triangle merging index syntax element specifying a first triangle merging candidate index. The first triangle merging candidate index indicates a first triangle merging candidate of a triangular shape-based motion compensation candidate list. The video decoder may determine whether the maximum number of triangle merging candidates is greater than 2. Based on the maximum number of triangle merging candidates not being greater than 2, the video decoder may infer that a second triangle merging candidate index indicates a second triangle merging candidate of the triangular shape-based motion compensation candidate list without obtaining any syntax element specifying the second triangle merging candidate index from the bitstream, the second triangle merging candidate being different from the first triangle merging candidate.

Abstract: An example device for decoding video data includes one or more processors implemented in circuitry and configured t: form first and second prediction blocks using first and second motion vectors and combine the first and second prediction blocks according to BDOF to form a final prediction block. For at least one sample location, the one or more processors are configured to determine that a first predictor for the at least one sample location is outside of a boundary of the first reference picture; determine that a second predictor for the at least one sample location is within a boundary of the second reference picture; set the first predictor equal to the second predictor; and determine a final BDOF value for a sample at the at least one sample location using the first predictor and the second predictor.

Abstract: An example device includes a memory and one or more processors implemented in circuitry and communicatively coupled to the memory. The one or more processors are configured to determine a value of a first syntax element indicative of a number of subpictures in a picture of video data. The one or more processors are configured to determine, for each subpicture among the subpictures in the picture, a value of a respective second syntax element indicative of an identification of a respective subpicture. The one or more processors are also configured to code the respective subpicture identified by the respective second syntax element.

Abstract: A data transmission system and an operation method thereof are provided. The data transmission system includes a host, a first device and a second device. The host is configured to set a voltage base of a transmission signal, and configured to pull down or up the transmission signal based on the voltage base of the transmission signal to form a plurality of glitches. The first device is connected to the host to receive the transmission signal. The first device obtains a digital content of the transmission signal according to the glitches, if the voltage base of the transmission signal is set as a first base. The second device is connected to the host to receive the transmission signal. The second device obtains the digital content of the transmission signal according to the glitches, if the voltage base of the transmission signal is set as a second base.

Abstract: For patient weight estimation in a medical imaging system, a patient model, such as a mesh, is fit to a depth image. One or more feature values are extracted from the fit patient model, reducing the noise and clutter in the values. The weight estimation is regressed from the extracted features.

Abstract: A video encoder and video decoder may determine to enable or disable a template-based inter prediction technique based on whether reference picture resampling or weighted prediction are used. A video encoder and video decoder may determine that a reference picture resampling mode is enabled. determine not to apply a template-based inter prediction technique to the video data based on the reference picture resampling mode being enabled, and code the video data using inter prediction without applying the template-based inter prediction technique.