Abstract: Techniques for determining predictions on a top-down representation of an environment based on vehicle action(s) are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) can capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle or a pedestrian). A multi-channel image representing a top-down view of the object(s) and the environment can be generated based on the sensor data, map data, and/or action data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) can be encoded in the image. Action data can represent a target lane, trajectory, etc. of the first vehicle. Multiple images can be generated representing the environment over time and input into a prediction system configured to output prediction probabilities associated with possible locations of the object(s) in the future, which may be based on the actions of the autonomous vehicle.

Abstract: Techniques are disclosed for updating map data. The techniques may include detecting a traffic light in a first image, determining, based at least in part on the traffic light detected in the first image, a proposed three-dimensional position of the traffic light in a three-dimensional coordinate system associated with map data. The proposed three-dimensional position may then be projected into a second image to determine a two-dimensional position of the traffic light in the second image and the second image may be annotated, as an annotated image, with a proposed traffic light location indicator associated with the traffic light. The techniques further include causing a display to display the annotated image to a user, receiving user input associated with the annotated images, and updating, as updated map data, the map data to include a position of the traffic light in the map data based at least in part on the user input.

Abstract: Disclosed is a deep discriminative network for person re-identification in an image or a video. Concatenation are carried out on different input images on a color channel by constructing a deep discriminative network, and an obtained splicing result is defined as an original difference space of different images. The original difference space is sent into a convolutional network. The network outputs the similarity between two input images by learning difference information in the original difference space, thereby realizing person re-identification. The features of an individual image are not learnt, and concatenation are carried out on input images on a color channel at the beginning, and difference information is learnt on an original space of the images by using a designed network. By introducing an Inception module and embedding the same into a model, the learning ability of a network can be improved, and a better differentiation effect can be achieved.

Abstract: An image feature extraction method for person re-identification includes performing person re-identification by means of aligned local descriptor extraction and graded global feature extraction; performing the aligned local descriptor extraction by processing an original image by affine transformation and performing a summation pooling operation on image block features of same regions to obtain an aligned local descriptor; reserving spatial information between inner blocks of the image for the aligned local descriptor; and performing the graded global feature extraction by grading a positioned pedestrian region block and solving a corresponding feature mean value to obtain a global feature. The method can resolve the problem of feature misalignment caused by posture changes of pedestrian, etc., and eliminate the effect of unrelated backgrounds on re-recognition, thus improving the precision and robustness of person re-identification.

Abstract: A bidirectional image-text retrieval method based on a multi-view joint embedding space includes: performing retrieval with reference to a semantic association relationship at a global level and a local level, obtaining the semantic association relationship at the global level and the local level in a frame-sentence view and a region-phrase view, and obtaining semantic association information in a global level subspace of frame and sentence in the frame-sentence view, obtaining semantic association information in a local level subspace of region and phrase in the region-phrase view, processing data by a dual-branch neural network in the two views to obtain an isomorphic feature and embedding the same in a common space, and using a constraint condition to reserve an original semantic relationship of the data during training, and merging the two semantic association relationships using multi-view merging and sorting to obtain a more accurate semantic similarity between data.

Abstract: A display panel, a manufacturing method thereof and a display device are provided. The display panel includes: a photosensitive sensor; a light shield layer disposed on a sensing side of the photosensitive sensor and including at least one first opening and at least one second opening, the first opening and the photosensitive sensor are overlapped with each other in a direction perpendicular to a surface of the display panel, so that light running through the first opening is irradiated to the photosensitive sensor; and an optical processing film disposed in a region of the light shield layer close to the second opening and on at least a portion of a surface of the light shield layer away from the photosensitive sensor, and a light reflectivity of the optical processing film is less than a light reflectivity of the light shield layer.

Abstract: A method and system for a software-defined camera. A device management center stores an intelligent application used for intelligent video analysis and stores intelligent application deployment files for various surveillance scenarios. The device management center sends a corresponding deployment file to a camera based on a location of a smart camera and an intelligent video analysis function that needs to be implemented. The camera obtains a corresponding intelligent application from the device management center based on a list of intelligent applications in the deployment file, to implement an intelligent video analysis function required in the surveillance scenario.

Abstract: A platinum/black phosphorus-carbon sphere methanol fuel cell anode catalyst and preparation method thereof including the following steps: (1) dispersing a black phosphorus solid in an organic solvent to obtain a single or a few layers of black phosphorus dispersion with set concentration; (2) mixing the dispersion with glucose and stirring until dissolved; (3) performing a hydrothermal reaction on the solution to obtain an aqueous solution of the composite material containing a carbon core black phosphorus shell structure; (4) uniformly mixing the aqueous solution with an ethylene glycol solution of sodium chloroplatinate, adjusting the pH, then reducing the platinum on the surface by using a microwave irradiation heating method; and (5) filtering, washing and drying the obtained composite material to obtain a platinum/black phosphorus-carbon sphere composite material.

Abstract: Provided are a method and system for implementing an SDO function, and a SDON system.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for blockchain-based file querying are provided. One of the methods includes: receiving a query request for a target file, the query request comprising identification information of a user and the target file; obtaining the target file based on the identification information of the user and the target file; providing a query page of the target file, the query page comprising interactive elements for selecting whether to upload the target file to a blockchain; receiving a user selecting to upload the target file to the blockchain; hashing the target file to generate a digital digest; signing the digital digest according to an asymmetric encryption algorithm using a private key associated with a cryptographic key pair to obtain a digital signature; and uploading the target file, the digital signature, and a public key associated with the cryptographic key pair.

Abstract: A precast segmental pier reinforced with both FRP bars and steel bars according to one or more embodiments of the present application includes a footing, a segmental pier, longitudinal bars and unbonded post-tensioned tendons, characterized in that: the segmental pier is comprised of one or more precast segments , the longitudinal bars are comprised of both the steel bar and the high-strength steel bar, connecting the footing and the segmental pier together with unbonded post-tensioned tendons to form an entire pier.

Abstract: Techniques for determining a vehicle action and controlling a vehicle to perform the vehicle action for navigating the vehicle in an environment can include determining a vehicle action, such as a lane change action, for a vehicle to perform in an environment. The vehicle can detect, based at least in part on sensor data, an object associated with a target lane associated with the lane change action sensor data. In some instances, the vehicle may determine attribute data associated with the object and input the attribute data to a machine-learned model that can output a yield score. Based on such a yield score, the vehicle may determine whether it is safe to perform the lane change action.

Abstract: An intra code-rate predicting method in video coding, which enables skipping of an entropy coding procedure during a rate-distribution optimization process and effectively reduces the coding time by modeling residual information of a prediction block and predicting the number of coding bits based on a model resulting from the modeling.

Abstract: A precast segmental pier reinforced with both conventional steel bars and high-strength steel bars according to one or more embodiments of the present invention includes a footing, a segmental pier, longitudinal bars and unbonded post-tensioned tendons, characterized in that: the segmental pier is comprised of one or more precast segments, the longitudinal bars are comprised of both the conventional steel bar and the high-strength steel bar, connecting the footing and the segmental pier together with unbonded post-tensioned tendons to form an entire pier.

Abstract: Techniques for determining predictions on a top-down representation of an environment based on vehicle action(s) are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) can capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle or a pedestrian). A multi-channel image representing a top-down view of the object(s) and the environment can be generated based on the sensor data, map data, and/or action data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) can be encoded in the image. Action data can represent a target lane, trajectory, etc. of the first vehicle. Multiple images can be generated representing the environment over time and input into a prediction system configured to output prediction probabilities associated with possible locations of the object(s) in the future, which may be based on the actions of the autonomous vehicle.

Abstract: The present invention discloses genes and SNP markers significantly associated with lint percentage trait in cotton, and use thereof. The genes significantly associated with the lint percentage trait in cotton are genes Gh_D05G1124, Gh_D05G0313, and GhWAKL3. In the present invention, a CottonSNP63K gene array is used for genotyping, and genome re-sequencing data are analyzed to identify SNP markers significantly associated with the lint percentage trait in cotton. Moreover, the present invention also discloses use of the genes and SNP markers, which are significantly associated with the lint percentage trait in cotton, in cotton germplasm identification, breeding, or genetic diversity analysis.

Abstract: Example proximity sensors are described. The proximity sensor can include a transceiver unit, and a leaky coaxial cable operably coupled to the transceiver unit. The proximity sensor described herein can be used with a steering wheel. For example, the leaky coaxial cable can be embedded in the steering wheel.

Abstract: A Collaborative Deep Network model method for pedestrian detection includes constructing a new collaborative multi-model learning framework to complete a classification process during pedestrian detection; and using an artificial neuron network to integrate judgment results of sub-classifiers in a collaborative model, and training the network by means of the method for machine learning, so that information fed back by sub-classifiers can be more effectively synthesized. A re-sampling method based on a K-means clustering algorithm can enhance the classification effect of each classifier in the collaborative model, and thus improves the overall classification effect.

Abstract: The present disclosure provides a hybrid framework-based image bit-depth expansion method and device. The invention fuses a traditional de-banding algorithm and a depth network-based learning algorithm, and can remove unnatural effects in an image flat area whilst more realistically restoring numerical information of missing bits. The method comprises the extraction of image flat areas, local adaptive pixel value adjustment-based flat area bit-depth expansion and convolutional neural network-based non-flat area bit-depth expansion. The present invention uses a learning-based method to train an effective depth network to solve the problem of realistically restoring missing bits, whilst using a simple and robust local adaptive pixel value adjustment method in an flat area to effectively inhibit unnatural effects in the flat area such as banding, a ringing and flat noise, improving subjective visual quality of the flat area.

Abstract: A multi-domain controller, a single-domain controller, a software defined optical network system and a method are disclosed.