35 results about "Map decoding" patented technology

The invention provides a satellite image and actually measured RSRP fused ground radio map generation system, and the system comprises a satellite image feature extraction module which is used for converting a high-resolution satellite image of a target region into high-dimensional image features reflecting the ground feature type distribution of the region; the base station physical characteristic input module is used for converting the physical parameters of the communication base station in the target area into characteristic vectors reflecting electromagnetic propagation characteristics; the multi-modal fusion module is used for fusing the high-dimensional image features and the feature vectors to generate joint feature representation; the radio map decoder is used for generating a radio signal power plane distribution diagram of the target area through a decoding network based on the joint feature representation; and the ground RSRP correction module is used for correcting the radio signal power plane distribution diagram output by the radio map decoder so as to output a final radio signal power distribution result. According to the invention, the space-ground collaborative data source fusion is realized to improve the mapping precision.

The invention provides an online map construction method and device fusing time sequence prior and historical global map prior, and relates to the technical field of online map construction.The method comprises the steps that time sequence BEV features and online generated BEV features are efficiently fused through multi-channel cross attention based on masks; adaptively fusing the time sequence enhanced BEV features and local BEV features provided by a historical map through a spatial prior gating network; a mixed prior ROI mask is generated through prior information provided by a time sequence and a historical global map, and initialization of map query in map decoding at the current moment is assisted, so that the reliability of online map construction is improved.

The present application relates to the technical field of communications, and discloses a gain map encoding method and apparatus, a gain map decoding method and apparatus, a device, and a medium. The method of the present application comprises: determining a first picture region and a second picture region in a gain map, the brightness of pixel points in the first picture region being greater than a first threshold, and the brightness of pixel points in the second picture region being less than or equal to the first threshold (S301); determining an encoding strategy of the gain map on the basis of the first picture region and the second picture region (S302); and encoding the gain map on the basis of the encoding strategy to obtain encoded information of the gain map (S303).

The invention provides a two-dimensional radio map generation system fusing communication base station and environment information, and the system comprises a base station encoder which is used for converting physical parameters of a communication base station in a target region into feature vectors reflecting electromagnetic rebroadcasting features; the environment encoder is used for converting the map of the target area containing the environment information into environment image features reflecting the global features of the target area; the environment image features and the feature vectors are fused to generate joint feature representation; and the radio map decoder is used for generating a radio signal power plane distribution diagram of the target area through a decoding network based on the joint feature representation. The accuracy of the two-dimensional radio map is effectively improved.

The invention belongs to the technical field of map construction, and discloses an online vectorization map construction method based on dynamic query management. Extracting perspective image features; generating aerial view view angle features based on the perspective image features; initializing map element query; inputting the initialized map element query and the aerial view view angle features into a map decoder based on dynamic query management, and optimizing the map element query; taking the output result of the Lth layer of the map decoder based on the dynamic query management as the final prediction of the attribute of the map element; and carrying out loss calculation and training. By optimizing and dynamically managing map queries in a map decoder, the computational consumption of low confidence map queries is effectively reduced. Under the same computing resources, the model is allowed to process a larger number of map queries, so that the construction precision of the vectorized map is improved. The research of automatic driving on-line map construction is further promoted, and the deployment of an on-line vectorization map model is facilitated.

The invention discloses a road detection method and system based on multi-frame information and a storage medium, and the method comprises the following steps: S1, transmitting continuous multi-frame image data collected by a camera at different moments into an encoder for feature extraction, and obtaining corresponding multi-frame advanced semantic features; s2, sending the multi-frame features obtained in the step S1 into a convolution unit based on long short-term memory (LSTM), so as to carry out recursive fusion and superposition on the multi-frame features in time sequence; s3, the fused features in the step S2 are sent to a decoder for feature map decoding; and S4, obtaining corresponding point coordinates according to the feature map obtained by decoding in the step S3. According to the method, the lane line and road boundary detection and extraction are carried out by combining the features of the multi-frame image, additional hardware does not need to be added, meanwhile, the operation speed can be kept within the actual application range, some complex scenes are solved, and the result is more accurate. The scheme is not only suitable for lane lines, but also can be applied to road boundaries and the like.

Systems and methods for error detection in quantum computing systems are provided. In one example, the method includes obtaining a multi-dimensional quantum error detection map. The multi-dimensional quantum error detection map represents one or more quantum error detection measurements over a period of time. The method includes determining a partitioning scheme and a fusion scheme for the multi-dimensional quantum error detection map based at least in part on the decoding delay and the fusion delay. The method includes partitioning the multi-dimensional quantum error detection map into a plurality of blocks based at least in part on the partitioning scheme. The method includes decoding each of the plurality of blocks. The method includes fusing the plurality of blocks into a decoded detection map based at least in part on the fusion scheme. The method includes operating a quantum computing system based at least in part on the decoded detection map.

To provide a device for efficiently encoding / decoding a feature map with a small processing amount.SOLUTION: The feature map decoding device 200 includes a feature map internal decoding unit for decoding the first single-scale feature maps that have been packed into frames and encoded to generate integer-type packed feature frames, and a feature map internal decoding unit for converting elements of the integer-type packed feature frames into decimal values to generate decimal-type packed feature frames. A feature map inverse transformation unit for generating a second single-scale feature map by dividing the second single-scale feature map into one or more packing groups based on information about the packing groups and unpacking the second single-scale feature map, a single-scale feature map refinement unit for generating a third single-scale feature map by calculating a distribution characteristic of the second single-scale feature map and refining the second single-scale feature map, and a feature map restoration unit for generating a multi-scale feature map by transforming the third single-scale feature map.SELECTED DRAWING: Figure 2

The present application relates to the technical field of communications. Disclosed are a gain map encoding method and apparatus, a gain map decoding method and apparatus, a device, and a medium. The encoding method of the present application comprises: acquiring at least one target image block in a gain map, the brightness of a pixel point in the target image block being greater than a first threshold (301); on the basis of the at least one target image block, determining identifier information of the target image block of the gain map and an image block group (302); and encoding the identifier information of the target image block and the image block group to obtain encoded information of the gain map (303).

A feature map decoding method according to the present disclosure may include decoding a metadata and the feature map; performing inverse conversion on a decoded feature map; and restoring features from inverse converted features. Here, a feature distortion compensation is performed on at least one of the decoded feature map, the inverse converted features or restored features.

This application discloses a land use change prediction method, apparatus, device, and medium based on map representation generation learning, relating to the fields of spatiotemporal big data mining and urban planning technology. The method includes: constructing multi-source map submaps and performing binarization and attention weighting to obtain binarized land use submaps and weighted geographic environment submap features; extracting deep aggregated spatial features from both to generate latent vector representations; flattening the representation into a one-dimensional feature sequence and querying the index of each element in a landscape codebook to form a vectorized index sequence; combining relative distance encoding, using a map sequence generation learning model to predict future vectorized index sequences, and querying the landscape codebook to obtain future vectorized tensors; iteratively decoding the tensor using a map decoder to generate land use change results. This application achieves more accurate land use change prediction by capturing mesoscale spatial local information and reducing unit-level error accumulation.

The application provides a vector map construction method and system based on prior map and multi-stage diffusion reasoning. A unified vector encoder is used to encode multiple prior maps to generate prior features. Real-time data obtained is converted into bird's-eye view features, and multi-stage diffusion reasoning is performed to map the bird's-eye view features of the degradation domain to diffusion features of the normal domain. The prior features and the diffusion features are fused to obtain fused features. The fused features are input into a constructed map decoder to generate an online vector map. In the scheme, multiple prior maps are introduced, and a unified vector encoder is used to efficiently encode different prior maps, thereby enhancing the robustness and accuracy of online map construction. Through multi-stage diffusion reasoning technology, image details are gradually optimized, which not only uniformly processes multiple image degradation problems, but also provides high-quality image restoration and enhancement effect in complex environments, thereby providing strong support for an automatic driving perception system.

A feature map encoding device (100) determines, from feature maps of a plurality of channels, an active channel to be encoded, generates one packing feature frame by packing only the feature map of the active channel, and generates a bit stream by encoding the packing feature frame.

The invention provides a priori map and multi-stage diffusion reasoning-based vector map construction method and system, and the method comprises the steps: carrying out the coding of a plurality of priori maps through employing a unified vector encoder, and generating priori features; and converting the obtained real-time data into bird's-eye view features, and executing multi-stage diffusion reasoning to map the bird's-eye view features of a degradation domain to diffusion features of a normal domain. And performing fusion processing on the prior features and the diffusion features to obtain fusion features. And inputting the fusion features into a constructed map decoder to generate an online vector map. According to the scheme, multiple prior maps are introduced, and different prior maps are efficiently coded by using the unified vector encoder, so that the robustness and accuracy of online map construction are enhanced. Through a multi-stage diffusion reasoning technology, image details are gradually optimized, various image degradation problems can be processed in a unified manner, high-quality image restoration and enhancement effects can be provided in a complex environment, and powerful support is provided for an automatic driving perception system.

A multi-layer feature map encoding method and device of the present disclosure comprises the steps of: acquiring a reduced feature map by reducing a multi-layer feature map extracted from an input image; and encoding the reduced feature map into a bitstream, wherein the reduction of the multi-layer feature map can be performed using a multi-layer feature map reduction means including a plurality of multi-layer feature map reduction blocks. In addition, the multi-layer feature map decoding method and device of the disclosure may comprise the steps of: acquiring a reduced feature map by decoding a bitstream; and restoring a multi-layer feature map by using the reduced feature map as an input of a multi-layer feature map restoration means including a plurality of multi-layer feature map restoration blocks.

This application provides a feature map encoding and decoding method and an apparatus, and relates to the field of artificial intelligence (AI)-based data encoding and decoding technologies. The feature map decoding method includes: obtaining a bitstream of a to-be-decoded feature map, where the to-be-decoded feature map includes a plurality of feature elements; obtaining a first probability estimation result corresponding to each feature element based on the bitstream, where the first probability estimation result includes a first peak probability; determining a set of first feature elements and a set of second feature elements from the plurality of feature elements based on a first threshold and the first peak probability corresponding to each feature element; and obtaining a decoded feature map based on the set of first feature elements and the set of second feature elements. This can improve encoding and decoding performance while reducing encoding and decoding complexity.

This application discloses a gain map encoding method and apparatus, a gain map decoding method and apparatus, a device, and a medium. The method of this application includes: determining a first picture region and a second picture region in a gain map, where a brightness of a pixel point in the first picture region is greater than a first threshold, and a brightness of a pixel point in the second picture region is less than or equal to the first threshold; determining an encoding strategy of the gain map based on the first picture region and the second picture region; and encoding the gain map based on the encoding strategy, to obtain encoded information of the gain map.

The invention discloses a lightweight on-line high-precision map construction method, device and system, and a storage medium. The method comprises the following steps: S1, a map decoder carries out refining processing on vehicle surrounding environment data by using SA and CA modules to construct a lightweight on-line high-precision map; s2, redundant structures existing in the SA module and the CA module are searched, and pruning is carried out by introducing mask variables; and meanwhile, refining and fine tuning are carried out on the pruned map decoder. By adopting the technical scheme of the invention, the model performance can be effectively maintained, and meanwhile, the calculation complexity and FLOPs are remarkably reduced, so that the reasoning efficiency of online high-precision map construction is improved.

To provide a device for efficiently encoding / decoding a feature map with a small processing amount.SOLUTION: In a feature map encoding device including a feature map reducing section, a feature map converting section, and a feature map internal encoding section, the feature map converting section 103 includes a range adjusting section that adjusts, for feature maps of a plurality of channels supplied from the feature map reducing section, feature amounts included in the feature maps on the basis of a parameter including a scaling coefficient and an offset coefficient, and a packing section that combines the feature maps of the plurality of channels into one frame to generate a packed feature frame, and the range adjusting section selects, for each element included in the parameter, whether encoding is performed in units of frames or in units of channels.SELECTED DRAWING: Figure 15

In the present invention, elements of a fractional feature map of each channel are quantized from a fractional type to an integer type to generate an integer feature map of each channel. The integer feature maps of each channel are packed to generate one integer packing feature frame. The integer packing feature frame is encoded to generate a bit stream. Linear quantization is performed according to a quantization mode suitable for each channel at the time of quantization.

The invention relates to a map generation method, a map generation device and a computer program product. The map generation method comprises the following steps: carrying out feature coding on vehicle environment information to obtain current aerial view features; obtaining an absolute position of the current aerial view feature according to the current self-parking space posture, and downloading a prior aerial view feature from a server according to the current aerial view feature and the absolute position; performing position correction on the current aerial view feature according to the prior aerial view feature to obtain a corrected current aerial view feature; fusing the corrected current aerial view feature and the prior aerial view feature to obtain a local aerial view feature; obtaining a plurality of map queries, and inputting the plurality of map queries and the local aerial view features into a pre-trained map decoder for processing to obtain a decoding result; and generating a plurality of map elements according to the decoding result, and generating a local map according to the plurality of map elements. According to the invention, the construction performance of the on-line vectorization high-precision map realized based on the vehicle can be improved.

This application discloses a gain map encoding method and apparatus, a gain map decoding method and apparatus, a device, and a medium, and pertains to the field of communication technologies. The method in this application includes: obtaining at least one target image block in a gain map, where a luminance value of a pixel in the target image block is greater than a first threshold (301); determining target image block identification information of the gain map and an image block group based on the at least one target image block (302); and encoding the target image block identification information and the image block group to obtain encoding information of the gain map (303).