Abstract: A video coding device receives a bitstream including video data. The device determines an intra-prediction mode subset. The intra-prediction mode subset include intra-prediction modes that correlate to a plurality of reference lines for a current image block and excludes intra-prediction modes that correlate to a primary reference line for the current image block. When a first intra-prediction mode is included in the intra-prediction mode subset, the device decodes the first intra-prediction mode by an alternative intra-prediction mode index. When the first intra-prediction mode is not included in the intra-prediction mode subset, the device decodes the first intra-prediction mode by an intra-prediction mode index. The device presents video data including an image block decoded based on the first intra-prediction mode.

Abstract: Apparatuses and methods for encoding and decoding are provided. The method for intra predicting a chroma sample of a block by applying cross-component linear model includes: obtaining reconstructed luma samples; determining maximum and minimum luma sample values based on the reconstructed luma samples; obtaining a difference of the maximum and minimum luma sample values. The method also includes: fetching a value out of a lookup table (LUT) by using a set of bits as an index, the set of bits following a position of the most-significant bit; obtaining linear model parameters based on the fetched value; and calculating a predicted chroma sample value by using the obtained linear model parameters. The efficiency to fetch the value out of the LUT is increased.

Abstract: A compact steel cord is provided. The cord includes a core-filament I steel wire with a diameter of d0, and four middle-layer M steel wires with a diameter of d1 and eight outer-layer O steel wires with a diameter of d2 that are twisted around the core-filament I steel wire in the same lay direction and the same lay length. Gaps L are reserved between the outer-layer O steel wires, an average width of the gaps L is not smaller than 0.02 mm, and the total size of the gaps L is larger than d0 and smaller than d1. The steel cord of a stable structure can be obtained by controlling the proportion of the sizes of all layers of monofilaments, the rubber coating performance of a tire cord can also be improved, the corrosion resistance, fatigue resistance, impact resistance and adhesion retention of a tire are improved.

Abstract: The present disclosure relates to encoding and decoding of a picture or a plurality of pictures (e.g. video) using a neural network which is partially trained online. Accordingly, at an encoder one or more layers are selected which are to be trained. Then, the training of the neural network is performed in which parameters of the selected layers are updated. The parameters of the remaining layers are maintained and not updated. The updated parameters are provided within a bitstream. The picture(s) is/are also encoded. The decoder receives an indication of the updated parameters, updates only those parameters indicated, and applies the so obtained neural network.

Abstract: This disclosure is directed to item-identifying carts that may be utilized by users to automatically identify items that the users place in their carts. In addition, these carts may automatically determine the outcome of respective events that occur with respect to these identified items. For example, the carts may be configured to identify one or more items that are placed into or removed from the cart, and thereafter determine one or more actions taken with respect to the identified items and a quantity of the items involved. For example, after identifying a first item and a second item either placed into or removed from the cart, the cart may determine that the user added two instances of the first item and removed one instance of the second item. In response to making this determination, the cart may update a virtual cart of a user operating the physical cart.

Abstract: A method of determining one or more candidate prediction modes, the method comprises deriving, by a processor, a first indicator by parsing a bitstream, wherein the first indicator specifies whether any affine model is a candidate motion model for an image block in a preset area; determining, by the processor, that the first indicator is set to 1; deriving, by the processor and based on the determination that the first indicator is set to 1, a second indicator by parsing the bitstream, wherein the second indicator specifies whether a 6-parameter affine model is a candidate motion model for the image block; and determining, by the processor, one or more candidate prediction modes for the image block based on the first indicator and the second indicator.

Abstract: A video coding mechanism is disclosed. The mechanism includes receiving a video signal partitioned into a chroma block and a first neighboring luma block. The mechanism also includes encoding prediction information for chroma samples of the chroma block into a bitstream. The prediction information for the chroma samples is determined via intra-prediction based on down-sampled neighboring luma samples. The down-sampled neighboring luma samples are generated from a single row of luma samples from the first neighboring luma block. A bitstream including the prediction information for the chroma samples is transmitted to support decoding and display of the chroma samples.

Abstract: In some examples, an electronic device includes a lid section including a first display area disposed on an interior side and a second display area disposed on an exterior side opposite to the interior side, where the interior side is disposed on a top side of a base section when the lid section is closed, and a display panel disposed within the lid section, the display panel including a first portion and a second portion, the first portion visible via the first display area and the second portion visible via the second display area.

Abstract: This application relates to the field of artificial intelligence (AI)-based video or picture compression technologies. The decoding method includes: performing probability estimation on input data by using a neural network, to obtain probability distribution of residual values of a plurality of samples and included in a residual of a current picture, where the input data includes at least a residual of a reference picture, and the reference picture is a decoded picture obtained before the current picture is decoded; performing arithmetic entropy decoding on a bitstream based on the probability distribution of the residual values of the plurality of samples and included in the residual of the current picture, to obtain first entropy decoding data, where the first entropy decoding data represents the residual of the current picture; and obtaining a reconstructed sample value of the current picture based on the residual of the current picture.

Abstract: This application provides a video picture prediction method and apparatus, to resolve a problem in a conventional technology that a length of a coded video sequence is increased. The first type of identifier may be added to a bitstream. The first type of identifier is used to indicate whether an affine motion model-based inter prediction mode is enabled for a video picture. For a video picture or a picture block included in the slice for which the affine motion model does not need to be used, a parameter, related to the affine motion model, of the picture block may not need to be transmitted. On a decoder side, during decoding of the picture block, the parameter related to the affine motion model does not need to be parsed. This can reduce load of a decoder, increase a processing speed, and decrease a processing time.

Abstract: A video coding device receives a bitstream including video data. The device determines an intra-prediction mode subset. The intra-prediction mode subset include intra-prediction modes that correlate to a plurality of reference lines for a current image block and excludes intra-prediction modes that correlate to a primary reference line for the current image block. When a first intra-prediction mode is included in the intra-prediction mode subset, the device decodes the first intra-prediction mode by an alternative intra-prediction mode index. When the first intra-prediction mode is not included in the intra-prediction mode subset, the device decodes the first intra-prediction mode by an intra-prediction mode index. The device presents video data including an image block decoded based on the first intra-prediction mode.

Abstract: This application discloses a picture display order determining method which includes: obtaining a decoding order index value of a current picture and a decoding order index value of a previous picture that is adjacent to the current picture according to a decoding order; adding 1 to a cycle identifier value when the decoding order index value of the current picture is less than the decoding order index value of the previous picture; and determining a display order index value of the current picture based on a sum of the decoding order index value of the current picture and a preset positive integer multiple of the cycle identifier value. In this application, the display order index value of the current picture progressively increases based on a display order index value of a picture that is located before the current picture according to the decoding order.

Abstract: An apparatus comprising a processor and memory including computer program code, the memory and computer program code configured to, with the processor, enable the apparatus at least to: generate, in respect of a road intersection, grouped probe data using probe data derived from probed vehicular movements through the road intersection, wherein the grouped probe data is generated by grouping together probe data comprising vehicle trajectories which have respective common heading angles at points of entry to and exit from the road intersection; and provide the grouped probe data for use in lane-level mapping of the road intersection.

Abstract: The present disclosure provides a photoacoustic image reconstruction method for suppressing artifacts, including: acquiring relevant parameters of the system; selecting a suitable pixel size and dividing the imaging area into multiple pixels; traversing each pixel, calculating multiple delay and summations according to the time sequence, and restoring the signal waveform; calculating the signal envelope of the signal recovered from each pixel, performing signal suppression, suppressing artifacts in the signal, and retaining real signal; the real signal value in the suppressed signal is taken as the gray value of the pixel in the image, and is saved in the picture to complete the reconstruction of the image.

Abstract: An intra prediction method by using cross component liner prediction mode (CCLM), includes: determining a luma block corresponding to a current chroma block; obtaining luma reference samples of the luma block based on determining L available chroma reference samples of the current chroma block, wherein the obtained luma reference samples of the luma block are down-sampled luma reference samples; calculating linear model coefficients based on the luma reference samples and chroma reference samples that correspond to the luma reference samples; and obtaining a prediction for the current chroma block based on the linear model coefficients and values of a down-sampled luma block of the luma block.

Abstract: In some examples, an electronic device includes a lid section including a first display area disposed on an interior side and a second display area disposed on an exterior side opposite to the interior side, where the interior side is disposed on a top side of a base section when the lid section is closed, and a display panel disposed within the lid section, the display panel including a first portion and a second portion, the first portion visible via the first display area and the second portion visible via the second display area.

Abstract: This application provides video picture prediction methods and apparatuses. In an implementation, a method for encoding of video picture comprises generating a bitstream for video signals, the bitstream comprises a plurality of syntax elements, wherein the plurality of syntax elements comprises a first identifier indicating that an affine motion model based motion compensation is enabled for a video sequence including a picture block to be processed, wherein a second identifier is conditionally signaled at least based on a value of the first identifier, wherein a false value of the second identifier indicates that a 6-parameter affine motion model based motion compensation is disabled for the video sequence, and wherein a true value of the second identifier indicates that the 6-parameter affine motion model based motion compensation is enabled for the video sequence.

Abstract: The technology of this application relates to an entropy encoding method that includes obtaining base layer information of a to-be-encoded picture block, where the base layer information corresponds to M samples in the picture block, and M is a positive integer, obtaining K elements corresponding to enhancement layer information of the picture block, where the enhancement layer information corresponds to N samples in the picture block, both K and N are positive integers, and N?M, inputting the base layer information into a neural network to obtain K groups of probability values, where the K groups of probability values correspond to the K elements, and any group of probability values is for representing probabilities of a plurality of candidate values of a corresponding element, and performing entropy encoding on the K elements based on the K groups of probability values.

Abstract: An intra prediction method includes obtaining respective intra prediction modes or texture distributions of P reconstructed picture blocks in a surrounding region of a current block; obtaining, based on the respective intra prediction modes or texture distributions of the P reconstructed picture blocks, Q priori candidate intra prediction modes of the current block and Q probability values; obtaining, based on M probability values corresponding to M priori candidate intra prediction modes, M weighting factors corresponding to the M priori candidate intra prediction modes; separately performing intra prediction based on the M priori candidate intra prediction modes to obtain M predicted values; and obtaining a predicted value of the current block based on a weighted summation of the M predicted values and the corresponding M weighting factors.

Abstract: A picture prediction method is provided, which includes: obtaining initial motion information of a current picture block; determining, based on a matching cost criterion, that positions of a pair of reference blocks are a position of a target forward reference block of the current picture block and a position of a target backward reference block of the current picture block, where positions of each pair of reference blocks include a position of a forward reference block and a position of a backward reference block; and for the positions of each pair of reference blocks, a first position offset and a second position offset are in a mirror relationship; and obtaining a predicted value of a pixel value of the current picture block based on a pixel value of the target forward reference block and a pixel value of the target backward reference block.