236results about How to "Reduce learning difficulty" patented technology

The invention provides a video super-resolution processing method and device, and the method comprises the steps: obtaining each frame of image of a video, and inputting the image into a convolutionalneural network; Sequentially performing feature extraction, feature dimension reduction, nonlinear mapping and high-dimensional space mapping on the image through the convolutional neural network toobtain super-resolution features; Performing reconstruction according to the features obtained by feature extraction and the super-resolution features to obtain a super-resolution image; And finally,performing coding to form a super-resolution video code stream. The super-resolution processing of the video is realized through the convolutional neural network; Dimension reduction through features,nonlinear mapping and high-dimensional space mapping are carried out; the calculation complexity is reduced, the time complexity is reduced, the network learning difficulty is reduced and the complextexture of the output image is reserved by adopting the jump connection, so that the high reconstruction quality is realized while the real-time performance required by video processing is ensured, and the method has a very wide application prospect in the fields of video real-time transmission and compression, video restoration and the like.

The invention relates to an input method. Based on a directional dot-dash input technology, touch tracks of 52 directional dots and dashes are optimized and are respectively expressed by using 52 directional dot-dash symbols; 52 times of touch tracks are expressed by one or n logic input partitions based on a touch screen; meanwhile, the corresponding relation between each directional dot-dash symbol and various candidate set symbols (comprising character symbols and function symbols) is allowed to be freely set, the corresponding candidate set symbols can be outputted after specified directional dot-dash symbols are inputted. According to the input method disclosed by the invention, off-screen touch typing of touch screen input is realized for the first time, so that the accuracy of dot-dash input can be ensured and the diversification of input contents can be met; in addition, the input method has the advantages of simple algorithm, high response speed and low power consumption. Bases on a 10-key Pinyin input method disclosed by the invention, at most 520 symbols (including initial consonants and compound vowels of Pinyin, simplicity, Pinyin auxiliary codes, strokes of Chinese Characters, English letters, number, punctuation symbols and the like) can be simultaneously input without switching an interface; in addition, each kind of symbol at most slide for the length of two key positions.

The invention discloses a video space-time super-resolution method and device based on improved deformable convolution correction. The method comprises the following steps: constructing a video space-time super-resolution network comprising a feature extraction module, an inter-frame correction module and an image reconstruction module; performing network parameter optimization on the video space-time super-resolution for later use; during application, using the feature extraction module for extracting feature maps from input low-fraction adjacent video frames, and using the inter-frame correction module for carrying out correction processing according to the feature maps corresponding to the adjacent video frames to synthesize an intermediate frame feature map; and performing inter-frame and intra-frame feature extraction on the input intermediate frame feature map and the feature map corresponding to the adjacent video frame by using an image reconstruction module, and reconstructing and outputting a high-resolution and high-frame-rate image sequence. By improving a deformable convolution mode and introducing explicit optical flow estimation, an attention network and other skills, an inter-frame correction network is enabled to be better competent for a video space-time super-resolution task, and a restoration effect is greatly improved.

The invention belongs to the field of digital image processing, and particularly relates to a residual neural network based on hole convolution and a two-stage image demosaicing method. According to the invention, a shallow feature extraction unit, a local residual unit and a deep feature extraction unit are introduced based on a residual neural network; the interaction of the three basic units greatly enhances the learning ability and modeling ability of the target neural network. Accurate mapping from the mosaic image to the RGB color image can be established for the image demosaicing problem, and finally the mosaic image in the Bayer CFA mode can be processed through the established effective mapping to obtain the RGB color image; meanwhile, a two-stage image demosaicing model is introduced, prior information is fully utilized, the modeling capability of the network is improved, and the understanding space is optimized; by means of the image demosaicing method, the peak signal-to-noise ratio of the image can be remarkably increased, the image demosaicing efficiency, quality and robustness are greatly improved, and the image demosaicing method has far-reaching significance in thefield of image processing.

The invention discloses a fixed-wing unmanned aerial vehicle autonomous control cooperation strategy training method, which comprises the following steps of (1) constructing a fixed-wing unmanned aerial vehicle control simulation environment Es based on dynamics, collecting real trajectory data of a pilot controlling an unmanned aerial vehicle, and learning in a supervised learning mode to obtainan unmanned aerial vehicle flight control strategy, (2) constructing a simplified abstract environment Ea from which flight control is stripped, creating two groups of unmanned aerial vehicle groups for grouping confrontation, and learning by using an APEX_QMIX algorithm to obtain a cooperation strategy, (3) combining the flight control strategy and the cooperation strategy in a layered reinforcement learning mode, and learning in a simulation environment Es to obtain a fusion strategy, and (3) migrating to a real environment. The method is of great significance in a real scene and has the advantages of being good in generalization, low in cost, high in robustness and the like.

The invention relates to a cloud platform architecture for an intelligent factory of a coal chemical enterprise and an implementation method thereof. the architecture comprises an IaaS layer, used forconverting physical resources formed by the infrastructure into a resource pool, providing operation environment support and data support for the PaaS layer in a resource management and scheduling mode, and providing data for the PaaS layer to establish a model base; a PaaS layer, used for modeling and storing a model base, an algorithm base and an industrial knowledge base, realizing managementof various micro-services based on a micro-service framework, realizing construction of coal chemical industry application service logic by utilizing a micro-service engine, and realizing constructionof a visual page through a development platform; and a SaaS layer, used for constructing a coal chemical industry application based on the PaaS layer and being open to other coal chemical industry enterprises through an industrial SaaS portal. According to the architecture, the graphical display page can be constructed through the platform, and finally, the application is constructed, so that thedevelopment process of an intelligent factory application system of a coal chemical industry enterprise is greatly shortened, the learning difficulty is reduced, the time cost and the labor cost aresaved, and the enterprise competitiveness is greatly improved.

The method is applicable to universal keyboard, dedicated keyboard, biservice keyboard, and handset keypad etc. digital keyboard. Based on former patent, this invention adds new technique, makes input method become more diversified, and more perfect. Spelling, strokes (patent ZL02119636.2, realizing input without coincident code on alphabetic keyboard, or digital keypad), and components input method are adopted in method of single click. Double spelling input method is adopted for operation of clicking keys at same time. Maximum four keys are pushed through one clicking by one hand, and maximum eight keys are pushed through one clicking by two hands. The method lowers difficulty to learn and operate corresponding method, raises input method. User does not need to learn new input method again by using different input devices. Chinese and English can be input quickly by using mode of clicking two push-keys on digit keyboard of handset etc. One clicking inputs one English letter.

The invention provides a priori knowledge guided robot operation skill learning system and method. The system comprises a physical environment module, an evaluation module and a robot operation skillpolicy learning module. The physical environment module collects robot operation environment information and a current operation state. The evaluation module evaluates a robot search operation policyby means of priori knowledge of an operation process and feeds back rewards and punishment values. The robot operation skill policy learning module learns an operation policy based on collected environment information, operation state and fed back rewards and punishment values to establish an expert knowledge base where operation contact states and actions of a mechanical arm are mapped one by oneso as to output a robot action decision, so that the learning efficiency is improved and the learning difficulty is reduced effectively.

The invention provides an AR locating learning method and apparatus, and relates to the technical field of information processing. The method comprises the steps of obtaining first image information,wherein the first image information is reality image information; obtaining second image information, wherein the second image information is template image information; matching the first image information with the second image information; and according to an AR locating algorithm, the first image information and the second image information, determining third image information, wherein the third image information is displayed on a display device. The technical problems of relatively long time of learning numerous keyboards, vapid and dull process and relatively high learning difficulty in the prior art are solved; and the technical effects of hand-eye synchronous teaching and greatly lowered learning difficulty are achieved.

The invention discloses a flight and maintenance simulator based on Prepar 3D. The flight and maintenance simulator based on Prepar 3D comprises a flight simulator, an aircraft maintenance simulator and an interactive client system. By the flight simulator, relevant training scenes such as aviation, navigation and land are established on the basis of a Prepar 3D platform. In the scenes, immersivetraining can be carried out in an extremely real environment. Prepar 3D can quickly build a simulation scene in a virtual world. The simulation scenes comprise an air conditioning system simulation model, an automatic driving system simulation model, a communication system simulation model and a power system simulation model; the virtual flight system based on Prepar 3D can be applied to teachingof flight and aircraft maintenance practice courses, can enable students to add a new learning way to learn in the multiple directions in an immersion manner and enable the students to comprehensivelyunderstand the structural characteristics, inspection processes, matters needing attention and the like of a whole aircraft before the students operate on a real aircraft, and thus, the benefit of classroom teaching is improved.

The invention relates to the all-one-code fast-record input method (ZL02119636.2) for general keyboard, special keyboard and mobile phone. This invention adds new technology to enrich input ways and allow one-time four keys for one hand or eight keys for two hands. This invention can improve input speed greatly, and fit to both Chinese and English.

The invention relates to a movable pet point-to-read machine. The current point-to-read machine utilizes a point-to-read pen to read an electronic book, has single style and no special playability, and can not attract children and keep the learning interest of the children for a long time. The movable pet point-to-read machine comprises a pet robot and a point-to-read machine, wherein the pet robot comprises a shell, an internal mechanical part and an electronic circuit; the shell is shaped like a pet, an animal, a cartoon character, a toy, and the like that are made of fluff, plastic, rubber or other fabrics; the mechanical part comprises a robot frame and a motor, wherein a voice control IC controls the motor in the robot frame according to beats of music or voice, and then the motor controls the mouth to open and close, hands to actuate and the body to swing by utilizing the rotation speed and the stoppage of the motor. The multifunctional pet point-to-read machine is combined with the robot toy with lovely sculpts by utilizing an acoustic control technique, plays music and learning knowledge, Chinese and English words, poetries, idiom stories, and the like, is safe and reliable, delicate in design, convenient and flexible to carry and use and convenient to popularize.

The invention discloses an optical orbital angular momentum machine learning recognition method based on a turbulence effect, and solves the problems that a huge training sample is needed when an existing machine learning method is used for recognizing an orbital angular momentum mode, and synchronous recognition of various turbulence environments is difficult to realize. The method comprises thesteps of obtaining a training sample under a numerical simulation condition; training a support vector machine multi-classification model with more optimized parameters by using a genetic algorithm and the feature vectors; performing orbital angular momentum recognition by using the trained support vector machine multi-classification model; and grouping joint identification is carried out on the images with a large identification range. According to the invention, a physical mechanism and machine learning are combined for optical orbital angular momentum identification. According to the method, the orbital angular momentum mode number of the vortex beam in various atmospheric turbulence environments can be effectively recognized, the accuracy is far higher than that of a traditional optical detection method, compared with a machine learning method based on an image algorithm, training samples can be effectively reduced, and the learning difficulty is lower. The optical orbital angularmomentum machine learning recognition method is used for free space optical communication.

The invention discloses a two-stage behavior identification method and system based on a key frame sequence and behavior information, and the method comprises the steps: screening out similar adjacent frames through calculating the similarity between sparse representation results of video frames, and obtaining a key frame sequence; calculating the similarity between the categories by using the behavior information of the behavior category label, and dividing all behavior categories into a plurality of large categories; establishing and training a two-stage behavior identification method model, wherein the first-stage training enables the network to have a rough classification capability, and the second-stage training enables the network to have a fine classification capability; and finally, identifying the video by using the trained model. According to the method, the key frame sequence of the video is acquired as input data, so that the key frame sequence contains more information; in addition, the network training process and the recognition process are divided into two stages by utilizing the information of the behavior category label, so that the learning process of the network is easier, and the recognition accuracy is improved.

The invention discloses an English training auxiliary system, which comprises a base; a sitting posture correction mechanism, a multi-mode learning mechanism, a stabilizing mechanism, a distance adjusting mechanism, a book pressing mechanism and a scanning mechanism are sequentially arranged on the base; the sitting posture correcting mechanism comprises a first sliding groove, a first telescopicrod, a sitting plate, a correcting backrest, an inclination sensor, an adjusting rod, a turbine, a first rotating shaft, a worm, a first motor, a first bevel gear and a second bevel gear. A first sliding groove is formed in one end of the upper surface of the base in an embedded mode. The interior of the first sliding groove is slidably connected with a distance adjusting mechanism. By arranging the sitting posture correcting mechanism, the sitting posture correcting mechanism can be automatically and scientifically adjusted, so that a child is in the optimal sitting posture, and the situationthat when the preprimary children carry out English training, due to the fact that the body is in the development stage, the poor sitting posture during English training easily affects the body development of the children is avoided; and thus the cervical vertebra and lumbar vertebra malformation development is avoided.

The invention relates to a font code and digital code general Chinese character input method re resolving project which is characterized in that it divides the stroke into ten strokes and the part into ten parts, then it uses them as core to design four font code and digital code general Chinese character input methods and uses the four input methods to form an integrated general Chinese character input method re resolving project of the denominator keyboard and the digital keyboard.

The invention relates to an FPGA development board. The FPGA development board comprises a Micro USB interface, a power module, an FPGA core chip and a peripheral module. The FPGA development board also comprises a downloading debugging module connected with the FPGA core chip, wherein the downloading debugging module comprises a communication module, a master controller and a peripheral circuit; the master controller is connected with the communication module and the peripheral circuit; and the communication module is provided with a USB2.0 interface. Through the FPGA development board, the learning difficulty of a user is lowered, the learning efficiency of the user is improved, the size of the FPGA development board is reduced, and user experience and usability are improved. The invention furthermore relates to a communication method of the FPGA development board.