Abstract: The present application provides a filtering method for intra-frame and inter-frame prediction. For a pixel value obtained by prediction, whether to filter a prediction block is self-adaptively determined by means of an RDO decision; and a filter is established based on a generalized Gaussian distribution function, and different filters are used for prediction blocks of different sizes, and filter parameters are obtained by training the prediction blocks of each size. The method comprises performing RDO on each coding unit on a coding end, and firstly performing intra-frame prediction or inter-frame prediction on each coding unit; then filtering the prediction block using the filtering method of the present invention, and determining whether to use prediction block filtering by means of an RDO decision; on a decoding end, configuring different filtering coefficients for different prediction block sizes; and decoding according to a flag.

Abstract: Disclosed is a multi-angle adaptive intra-frame prediction-based point cloud attribute compression method. A novel block structure-based intra-frame prediction scheme is provided for point cloud attribute information, where six prediction modes are provided to reduce information redundancy among different coding blocks and improve the point cloud attribute compression performance. The method comprises: (1) inputting a point cloud; (2) performing point cloud attribute color space conversion; (3) dividing a point cloud by using a K-dimensional (KD) tree to obtain coding blocks; (4) performing block structure-based multi-angle adaptive intra-frame prediction; (5) performing intra-frame prediction mode decision; and (6) performing conversion, uniform quantization, and entropy encoding.

Abstract: The present application provides a filtering method for intra-frame and inter-frame prediction. For a pixel value obtained by prediction, whether to filter a prediction block is self-adaptively determined by means of an RDO decision; and a filter is established based on a generalized Gaussian distribution function, and different filters are used for prediction blocks of different sizes, and filter parameters are obtained by training the prediction blocks of each size. The method comprises performing RDO on each coding unit on a coding end, and firstly performing intra-frame prediction or inter-frame prediction on each coding unit; then filtering the prediction block using the filtering method of the present invention, and determining whether to use prediction block filtering by means of an RDO decision; on a decoding end, configuring different filtering coefficients for different prediction block sizes; and decoding according to a flag.

Abstract: A sampling probe, an automatic sampling device, and a container detection system are provided. The sampling probe includes: a mounting base; a housing mounted on the mounting base, a first accommodation chamber having an opening being defined in the housing, and an exhaust hole in communication with the first accommodation chamber and outside of the housing being formed in the housing; a coupling portion formed on an outer edge of the opening of the first accommodation chamber and formed to be hermetically coupled with an air outlet of a container; and a suction device mounted on the housing and configured to suck gas in the container into the first accommodation chamber through the air outlet. The sampling probe may collect the odor of toxic and harmful gases/hazardous chemicals inside the container at the air outlet of the container, without destroying the overall structure of the container.

Abstract: The present disclosure provides a trace detection device. The trace detection device includes: a box body comprising a main body frame and a top plate, the top plate and the main body frame forming a fully enclosed cavity; an ion migration tube assembly in the cavity and on a first side of the cavity; and a preamplifier and high voltage circuit board in the cavity and on a second side of the cavity, the second side being opposite to the first side.

Abstract: The invention discloses a point cloud geometric compression method based on a depth auto-encoder, which comprises the following steps of: (1) point cloud preprocessing: collecting a type of point cloud to be compressed as a training set, and normalizing the training set into a unit circle; (2) point cloud down-sampling: down-sampling the point clouds in the training set so that each point cloud have the same point number m and each point in the point cloud has (x, y, z) three-dimensional coordinates; and adopting a farthest point down-sampling method by randomly selecting a point for the first time and then selecting the point farthest away from the selected point set every time to add into the selected point set until the selected point number meets the requirement; (3) training a compression model: inputting the point cloud sampled in step (2) into a point cloud geometric compression framework based on a depth auto-encoder for training; and (4) geometric compression of the point cloud: applying the trained

Abstract: An enhanced graph transformation-based point cloud attribute compression method. For point cloud attribute information, a point cloud is first subjected to airspace division by using a K-dimension (KD) tree; a new graph transformation processing method in combination with spectral analysis is provided; the point cloud is then subjected to spectral clustering on graphs in coded blocks of the point cloud; expansion is performed on the basis of existing graph transformation to implement a local graph transformation scheme; enhanced graph transformation with two transformation modes is formed; the compression performance of graph transformation is improved. The method comprises: performing color space transformation of point cloud attributes; dividing the point cloud by using the KD tree to obtain the coded blocks; performing spectral clustering-based enhanced graph transformation; performing transformation mode decision; and performing uniform quantization and entropy coding.

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: An intra-frame prediction-based point cloud attribute compression method. A new block structure-based intra-frame prediction scheme is provided for point cloud attribute information, where four prediction modes are provided to reduce information redundancy among different coding blocks as much as possible and improve point cloud attribute compression performance. The method comprises: performing point cloud attribute color space conversion; dividing a point cloud by using a K-dimensional (KD) tree to obtain coding blocks; performing block structure-based intra-frame prediction; performing intra-frame prediction mode division; performing conversion, uniform quantization, and entropy coding.

Abstract: The present invention discloses a wiping-type sample sampling and feeding device, a card reading apparatus, and a gate machine apparatus. The wiping-type sample sampling and feeding device comprises a thermally desorbing portion for analyzing a substance; a wiping-type sampling portion for wiping the substance on a card or certificate and includes a first wheel, a second wheel and a wiping conveyor belt that travels between the first and second wheels along a first direction; and a card/certificate conveyor portion including a card carrying belt configured to convey a card or certificate along a second direction so that the card or certificate can contact with the wiping conveyor belt during conveyance of the card or certificate, thereby the wiping conveyor belt wipes a surface of the card or certificate, wherein the second direction is substantially perpendicular to the first direction.

Abstract: Disclosed is a boundary filtering method for intra prediction, relating to the video encoding technology filed. Whether boundary filtering is performed on an intra prediction block or not is adaptively selected by means of a rate distortion optimization decision; during filtering, a filter coefficient exponentially attenuated relative to distance to boundary is adopted to perform filtering on the first N rows or the first N columns of the intra prediction block by means of an intra prediction block filter, and different filtering strengths are used according to different sizes of the prediction blocks. Therefore, the boundary distortion problem of intra prediction block is solved, the intra prediction precision is improved, and the encoding efficiency of intra prediction block is increased; and the practicability and the robustness of the boundary filtering technology are improved.

Abstract: An intra-frame and inter-frame combined prediction method for P frames or B frames. The method comprises: self-adaptively selecting by means of a rate-distortion optimization (RDO) decision whether to use the intra-frame and inter-frame combined prediction or not; using a method for weighting an intra prediction block and an inter prediction block in the intra-frame and inter-frame combined prediction to obtain a final prediction block; and obtaining the weighting coefficient of the intra prediction block and the inter prediction block according to prediction distortion statistics of the prediction method. Therefore, prediction precision can be improved, and coding and decoding efficiency of the prediction blocks are improved.

Abstract: A sampling device and an inspection apparatus are disclosed. In one aspect, an example gathering and sampling device includes a cylindrical outer housing and an inner housing disposed within the cylindrical outer housing, a cyclone chamber is formed between the cylindrical outer housing and the inner housing to generate a cyclone by injecting a gas flow into the cyclone chamber. The gathering and sampling device further includes an outer chamber body, and a plurality of gas injection orifices formed in the first inner housing end opening of the inner housing and configured to inject a gas towards a substantial center of a circular region defined by an end face of the first outer housing end opening of the cylindrical outer housing.

Abstract: It is disclosed a scrubbing and sampling device, a card reader apparatus and a gate apparatus. The scrubbing and sampling device includes: a scrubbing and sampling portion including a first wheel and a second wheel, which are respectively capable of rotating around respective rotating axes, and a scrubbing conveyor belt tensioned by the first wheel and the second wheel and driven by rotation of the first wheel and the second wheel, to move between them; and an desorbing portion configured to desorb properties of an sample that is conveyed into the desorbing portion. The scrubbing conveyor belt is configured to move through the desorbing portion such that the desorbing portion desorbs the sample on the scrubbing conveyor belt when the scrubbing conveyor belt enters the desorbing portion.

Abstract: The present disclosure discloses a gas chromatograph-ion mobility spectrometry combined equipment, including: a gas chromatograph device for pre-separating a to-be-detected sample to form a pre-separated sample; an ion mobility spectrometry device in fluid communication with an outlet of the gas chromatograph device for detecting the pre-separated sample; and a gas circulating device in fluid communication with a discharged gas interface of the ion mobility spectrometry device for processing a discharged gas from the ion mobility spectrometry device, wherein the gas circulating device is further in gas communication with the gas chromatograph device for conveying a part of the discharged gas to the gas chromatograph device to serve as a carrier gas, which drives the to-be-detected sample to enter the gas chromatograph device. The miniaturization and the portability of the gas chromatograph-ion mobility spectrometry combined equipment are improved.

Abstract: A cross-media search method using a VGG convolutional neural network (VGG net) to extract image features. The 4096-dimensional feature of a seventh fully-connected layer (fc7) in the VGG net, after processing by a ReLU activation function, serves as image features. A Fisher Vector based on Word2vec is utilized to extract text features. Semantic matching is performed on heterogeneous images and the text features by means of logistic regression. A correlation between the two heterogeneous features, which are images and text, is found by means of semantic matching based on logistic regression, and thus cross-media search is achieved. The feature extraction method can effectively indicate deep semantics of image and text, improve cross-media search accuracy, and thus greatly improve the cross-media search effect.

Abstract: Embodiments of the present disclosure provide an ion mobility spectrometer device. The ion mobility spectrometer device includes: an ion mobility tube, a sampling device, and a sampling and circulating gas path. The sampling device includes a solid sample desorption device and a gas sampling device. The solid sample desorption device is configured to process the solid sample into a first mixed gas containing the solid sample, and the gas sampling device is configured to process the gas sample into a second mixed gas containing the gas sample. The sampling and circulating gas path is configured to transfer the first mixed gas and/or the second mixed gas into the ion mobility tube for detection.

Abstract: A method for image matching includes acquiring a template image and a target image; acquiring a group of template features according to the template image; extracting a group of target features according to the target image; and according to template features and target features, calculating an degree of image similarity between the template image and each frame of target images, and using a target image with the maximum degree of image similarity as a matched image to the template image. In the image-matching method, image matching is performed by calculating an degree of image similarity between a template image and each target image according to a degree of image similarity between template features and target features, so that non-redundancy of features in an image matching process and correct image matching can be guaranteed, and the image matching accuracy can be improved.

Abstract: A microneedle chip and manufacturing method. The method comprises injecting, into a female mold, a fluid needle liquid, wherein forming cavities matching the shapes of needles of a microneedle chip are provided at the female mold and form a cavity array, injection inlets are provided at a surface of one side of the female mold, and air ejection openings are provided at a surface of another side of the female mold to form an air ejection surface; covering the air ejection surface of the female mold using a breathable film, and during injection, passing a gas through the breathable film so as to retain the liquid inside the forming cavities; curing the fluid needle liquid to form the microneedle chip, and demolding to obtain the same. By employing the air ejection openings and the breathable film, a liquid is retained while ejecting a gas, providing a favorable micro-injection effect.

Abstract: Provided is a method for detecting a violent incident in a video based on a hypergraph transition model, comprising a procedure of extracting a foreground target track, a procedure of establishing a hypergraph and a similarity measure, and a procedure of constructing a hypergraph transition descriptor; using the hypergraph to describe a spatial relationship of feature points, in order to reflect attitude information about a movement; and modelling the transition of correlative hypergraphs in a time sequence and extracting a feature descriptor HVC, wherein same can effectively reflect the intensity and stability of the movement. The method firstly analyses the spatial relationship of the feature points and a transition condition of a feature point group, and then performs conjoint analysis on same. The method of the present invention is sensitive to disorderly and irregular behaviours in a video, wherein same is applicable to the detection of violent incidents.