43 results about "Visual cortex" patented technology

The invention belongs to the technical field of intelligent control of robots, and discloses a self-adaptive adjustment system for behavior modes of an intelligent robot with a body, which comprises a neuromorphic sensing module for acquiring and fusing multi-mode environment sensing information, performing space-time compression on the multi-mode environment sensing information by referring to a brain visual cortex sparse coding principle, and generating a neural network; generating an environment state representation vector, and constructing a neuromorphic perception path; the cognitive constraint decision module is used for generating an action strategy by adopting a neural symbol hybrid architecture based on the environment state representation vector; through a cognitive momentum optimization mechanism, a strategy inertia item is introduced to improve an updating process of an action strategy parameter, and a behavior decision vector is obtained; the variable impedance execution module is used for mapping the behavior decision vector into a plurality of virtual muscle cooperation elements through a muscle cooperation mapping rule, and solving an expected movement track of each execution joint of the robot; and the intelligent robot with the body has higher adaptability, stability and execution capability.

The embodiment of the invention provides a voxel-level semantic mapping method for a human visual cortex, and the method comprises the steps: building a corresponding relation between a visual stimulation feature and a human brain voxel response through a visual language model and a coding model; adopting a BLIP image description generation and word segmentation technology to extract a plurality of noun candidate tags from a human brain image sample set highly responsive to target human brain voxels; generating a plurality of image samples consistent with the plurality of noun-type candidate tags in terms of semantics in batches, and inputting the image samples into the coding model for response evaluation; and by sorting the voxel responses of the plurality of image samples, distributing semantic correlation scores for the plurality of noun type candidate tags. According to the voxel-level semantic mapping method for the human visual cortex provided by the embodiment of the invention, the label bias can be reduced by utilizing the visual language model by constructing a voxel-level semantic mapping mechanism running in an open vocabulary space. The embodiment of the invention further provides a voxel-level semantic mapping device and electronic equipment.

The invention discloses a multi-scale pulse gated image rain removal method and system with biological inspiration, and the method comprises the steps: firstly obtaining a synthetic data set of a rain removal task of a single image, and carrying out the preprocessing; secondly, a bionic driving color antagonism feature extraction mechanism is introduced, separation and enhanced expression of color degradation information in a rainy day image are achieved, and color antagonism features are obtained; then performing structure enhancement and multi-scale abstraction on the color antagonism features through bionic visual cortex multi-scale coding, and constructing visual cortex feature representation; and finally, for visual cortex feature representation, proposing a bionic visual cortex dual-channel prediction structure and a hybrid coding reconstruction structure, and outputting an image rain removal result graph. And constructing a multi-target mixed loss function, and carrying out reverse training and testing. According to the invention, the color information and the brightness information are accurately separated, the interference of background noise on the target color is reduced, and image rain removal is accurately and efficiently realized.

The invention discloses a retinal vessel segmentation and lesion detection method based on incremental learning. The method comprises the specific steps that firstly, an original image of a data set STARE is acquired, and preprocessing such as segmentation and data enhancement is carried out on an original retina image; then, a VGAT-Net-IL network model is constructed, the network takes a coding-decoding symmetric structure as a trunk, a visual cortex mechanism is simulated through an adaptive receptive field module to dynamically adjust a receptive field, and local details and global features of the retinal vessels are cooperatively extracted; meanwhile, a dynamic bimodal attention module is innovatively integrated, variable convolution is introduced into the dynamic bimodal attention module to adaptively adjust a sampling position, a blood vessel region is precisely focused in combination with a space and channel attention mechanism, and after the dynamic bimodal attention module, a Bayesian semantic association module is introduced to generate features containing semantic association; in order to solve the problem that old knowledge is easy to forget when a model learns new lesion features, an incremental learning technology training model is introduced. According to the method, the retinal vessel segmentation precision and the lesion detection capability are improved, and a reliable image analysis basis is provided for retinal disease diagnosis.

The application relates to a high-definition image explainable classification method and device, computer equipment and a storage medium. The method simulates the process of image perception, feature extraction, inductive reasoning and learning of the human brain. The method is based on the latent space of a pre-trained StyleGAN, a conversion network is designed to simulate the feature extraction of the visual cortex of the brain, effectively converting high-dimensional latent encoding into low-dimensional and decoupled classification features, and the problems of rule explosion and calculation collapse are alleviated; a fuzzy neural network is used to simulate the reasoning function of the parietal lobe and the prefrontal cortex of the brain, and an improved method of the fuzzy neural network structure suitable for the high-definition image explainable classification model is designed, so that the explainable classification of the low-dimensional features is realized; the fuzzy rules used for classification are visually displayed and analyzed, and a feature visualization method is designed based on the pre-trained StyleGAN generator, so that the explainability is further improved.

The invention belongs to the field of emotion generation simulation, and provides an audiovisual emotion generation method for neuroanatomy alignment, which comprises the following steps: step 1, a visual module simulates a brain visual cortex function and processes visual emotion data; 2, simulating a brain auditory cortex function by an auditory module, and processing audio emotion data; step 3, the fusion module simulates an audio-visual fusion function of anterior temporal superior gyrus areas on both sides of the brain, integrates output signals of the visual module and the auditory module, and generates a comprehensive feature vector; 4, the BEL module simulates an emotional interaction mechanism of the brain amygdala kernel and orbital frontal cortex, and bionic emotion learning and generation are completed based on the comprehensive feature vector; 5, comparing the EPP value of the generated data with the EPP value of the original data, and verifying the interpretability of emotion generation; according to the method, brain emotion learning and generation bionic mechanisms are improved through an integrated modular component of neuroanatomy alignment, and the interpretability of an audiovisual emotion generation model is improved.

The present application is based on the recognition process of human visual cortex observation-exercise-perfection, and proposes a mosaic text recognition method: synthetic data and public benchmark data sets are used to construct original image-mosaic image data pairs; first, the mosaic image data is sent to the image encoder in the "observation" module to extract features hierarchically; then, the image is preliminarily restored through the reconstruction module; inspired by the mask autoregressive encoder, self-supervised learning is used to simulate the "exercise" process of human beings, and the visual self-attention module is used to predict the pixel value; finally, the denoising diffusion probability model of the "perfection" module trains the U-shaped neural network to predict the noise of each step to realize iterative optimization; the weight parameters are optimized by back propagation; and the open source recognition network or cloud service API is used to recognize the character sequence. The present application provides a thought and feasible scheme for the problem of multi-lingual mosaic text image recognition.

The invention discloses a brain-like vision-based dynamic following method for an unmanned aerial vehicle to inspect a fan blade, and the method comprises the steps: collecting a fan blade image by an unmanned aerial vehicle; a brain-like visual perception method composed of a V1 primary visual cortex model and an MT intermediate temporal lobe region model and a visual perception method composed of a V2 visual cortex and a V4 visual cortex are combined to perceive and track a target in an image, and finally, the predicted position of the target is obtained through PFC. According to the method, the real-time calculation complexity during yaw change of the fan blade pose can be effectively reduced, and the stable following precision of the unmanned aerial vehicle to the fan blade is improved.

The invention discloses a wireless photovoltaic visual cortex prosthesis system and method for total-blindness visual reconstruction, and the system comprises an external image processing unit which is used for collecting an environment image and generating a corresponding optical stimulation pattern; the near-infrared projection unit is connected with the external image processing unit and is used for converting the optical stimulation pattern into a near-infrared light stimulation sequence; the optical transparent cranial window assembly is used for transmitting the near-infrared light stimulation sequence to the visual cortex; and the flexible photovoltaic stimulation array is used for receiving the near-infrared light stimulation sequence through the optical transparent cranial window assembly and directly converting the near-infrared light stimulation sequence into an electrical stimulation signal for stimulating the primary visual cortex V1. By combining the flexible photovoltaic stimulation array with the optical transparent cranial window assembly, a wireless photoelectric link from the outside to the primary visual cortex is constructed, and a solution for reconstructing functional vision by directly stimulating the cortex without a leather-covered cable is provided for all-blind patients.

The invention discloses a bionic visual information perception method and system based on semantic driving. The method comprises the steps that scene image information containing target content is acquired; performing semantic analysis on the scene image information to extract high-level semantic information, and calculating a high-level semantic weight based on the high-level semantic information; identifying visual features of the scene image information, and fusing the visual features and the high-level semantic weight to screen out key information pixels from the scene image information; mapping the key information pixel into a corresponding cortical electrode number based on a topological corresponding relation between a preset visual space and a visual cortical layer, and generating a stimulation vector corresponding to the cortical electrode number; and outputting the cortical electrode number and the stimulation vector to bionic visual stimulation equipment so as to realize perception of the scene image information by a user. Through a semantic-driven key information pixel screening and structured expression mechanism, efficient transmission of facial expressions and text information is realized under the limitation of a low-pixel channel.

A large-scale visual cortex neural network simulation method based on the concept of virtual synapses involves brain-like computing, neural network modeling and simulation. The synaptic conductance calculation strategy of "virtual synapses" is used to reduce the independence of the calculation process of each state variable, and the neuron parameter update is synchronized by multiple threads with the help of the CUDA computing platform. The synaptic conductance calculation strategy of "virtual synapses" is used. "Virtual synapses" are the integration of synaptic inputs received by postsynaptic neurons. Each postsynaptic neuron has n "virtual synapses". When simulating large-scale neural networks, the present invention reduces the huge synaptic current calculation process and reduces the independence of the calculation process of each state variable to save memory usage and reduce time consumption.

This disclosure relates to a method, system, device, and medium for processing visual cortex photoelectrostimulation. The method includes: acquiring a visual stimulus pattern; determining a mathematical model based on the visual stimulus pattern; generating a visual stimulus signal of a target paradigm according to the mathematical model; acquiring the user's electroencephalogram (EEG) signal and eye and / or pupil response signal corresponding to the visual stimulus signal; processing the response signal to obtain a visual cortex response signal of a target format; acquiring the EEG signal and visual cortex response signal under multiple different target paradigms; selecting different processing methods to extract features from the EEG signal and visual cortex response signal according to different target paradigms to obtain multiple target features; evaluating based on the multiple target features to obtain an evaluation result; and displaying the evaluation result in the form of charts and numerical values ​​on the user terminal interface. This technical solution combines multiple advanced stimulus generation, recording, and analysis methods, making it suitable for various scenarios.

The invention discloses an intelligent head-mounted device for sleep improvement in the technical field of sleep-aiding physiotherapy, and the device comprises a flexible patch group which is used for being attached to the skin surface of the head of a user; the flexible patch set comprises a pillow area flexible patch, a forehead area flexible patch and bilateral temporal area flexible patches, wherein the forehead area flexible patch and the bilateral temporal area flexible patches are symmetrically arranged. The pillow area flexible patch is used for providing stable support when a user lies on the back and stimulating a visual cortex and an afterbrain area related to sleep regulation; each flexible patch comprises a self-adaptive interface layer, a substrate layer, a multi-mode stimulation module, a physiological signal sensor and a control module which are laid from bottom to top. The problems of wearing compression and displacement in sleep are solved through the distributed flexible patch and the self-adaptive interface layer, the sleeping efficiency and the sleeping depth are remarkably improved, and individuation and self-adaptive optimization of intervention parameters are achieved; and finally, sleep improvement experience integrating extreme comfort, efficient intervention, stability, reliability and continuous intelligent evolution is provided for the user.

The invention relates to a visual closed-loop diagnosis and treatment system based on electrical stimulation, and the system comprises an image collection module which is used for collecting external video image information; the image processing module is used for processing and coding the received video image information into a nerve electrical stimulation coding signal and sending the nerve electrical stimulation coding signal to the electrical stimulation control module; the electrical stimulation control module is softly attached to the visual cortex of the brain of the patient or the animal, and is used for further processing the received electrical nerve stimulation coding signal, outputting a corresponding electrical stimulation parameter and controlling a corresponding flexible electrode to output an electrical signal to stimulate nerve cells; and the stimulation effect evaluation module is used for collecting the biomarker concentration of the patient and evaluating the safety and effectiveness of electrical stimulation after data analysis. According to the visual diagnosis and treatment closed-loop system based on electrical stimulation, the effect of residual vision protection is achieved by setting safe and accurate electrical stimulation parameters, a feedback closed loop is formed through the stimulation effect evaluation module, and the safety and effectiveness of stimulation are effectively improved.

The invention discloses a visual reconstruction method and a related product. The method comprises the following steps: acquiring image data of a target image; mapping the coordinate of each visual pixel in the image data and a visual cortex to obtain an array matrix; the array matrix comprises a mapping relation between each visual pixel and a visual cortex; based on the sound focus position corresponding to each visual pixel in the image data, obtaining a driving parameter of each array element in the stimulation equipment; processing the array matrix based on the driving parameter of each array element to obtain a driving sequence; and controlling stimulation equipment based on the driving sequence, and stimulating the visual cortex to present the target image. The defect that traditional single-point or uniform scanning stimulation lacks space coding capacity is effectively overcome, the spatial resolution and perception consistency of artificial vision are remarkably improved through topological mapping from an image to a cortex layer and accurate regulation and control of a sound field, and meanwhile long-term foreign matter reaction is avoided.

The invention provides a biological brain neuron activation mechanism analysis method and device oriented to visual search. A mouse is taken as a model animal, (1) a neuron activation analysis method based on target stimulation correlation is provided, and the representation problem of a sparse activation mechanism of visual cortical neurons is solved; (2) a neuron activity pattern analysis method based on mouse visual brain region function hierarchy division is provided, and the problem of representation of a hierarchical activation mechanism of visual cortical neurons is solved; and (3) a contrast experiment of background noise is introduced into visual stimulation, so that the representation problem of a visual cortical neuron activation distribution rule under the influence of the background stimulation noise is solved.

The invention discloses a wireless visual cortex reconstruction method and device based on optogenetics. The method comprises the steps that selective expression of red-shift light-sensitive channel protein is limited to neurons of a primary visual cortex V1 area; establishing an optical channel in a V1 area of the primary visual cortex corresponding to the skull; environment visual information is wirelessly collected, and nerve mapping conversion is carried out; red light stimulation is projected to the V1 area of the primary visual cortex through an optical channel by adopting a time sequence framing regulation and control strategy; a dynamic safety regulation and control mechanism is implemented, and photostimulation parameters are adjusted in real time according to physiological response and physical parameters. Through cooperation of V1 area red-shift light-sensitive channel protein expression, optical channel establishment, accurate nerve mapping conversion, time sequence framing red light stimulation and dynamic regulation and control, wireless visual reconstruction which does not need electronic device implantation, has single-neuron-level resolution and is safe and stable for a long time is provided for a completely blind patient.

The invention discloses a multi-modal joint evaluation method for the repairing effect of an eye-brain assembly, and belongs to the technical field of biomedical engineering and neuroscience. The method aims at solving the problems that an existing evaluation means cannot reflect function integration in real time in a living body state, a specific index is lacked to distinguish effective remodeling and disordered growth, and a single behavioral test is prone to interference, so that false positive is caused. Specific visual stimulation is presented to a transplantation receptor, local field potential of a primary visual cortex is synchronously collected, and Low Gamma frequency band signals are extracted to calculate direction selectivity indexes and brain network topological attributes; meanwhile, a hierarchical visual behavioral test for sensing spatial cognition from basic light is carried out; and finally, constructing a binary decision matrix based on thresholding scores of electrophysiology and behavioral indexes, and outputting a four-classification quantitative evaluation conclusion including effective functional repair, thereby realizing accurate and standardized judgment of the visual cortex repair effect.

To greatly reduce fear and mental burden of an injection object person to injection work.SOLUTION: A shielding portion 2 that shields an injection operation on an arm from a visual cortex of a person to be injected when being disposed in the vicinity of the arm 100 of the person to be injected, a contact portion 3 that is provided on the shielding portion 2 so as to be capable of being brought into contact with and separated from the arm 100, and a pattern 5 that is displayed on at least one of the shielding portion 2 and the contact portion 3 and expresses the inevitability that the contact portion 3 dynamically comes into contact with the arm 100, the pattern 5 is expressed so that the contact part 3 contacts the arm 100 as a part of the living thing.SELECTED DRAWING: Figure 4

The invention relates to a visual cortical nerve regulation and control method based on theta explosive type transcranial magnetic stimulation, the method adopts a magnetic resonance guided MNI coordinate system to position an occipital pole stimulation area, the visual cortical layer is a primary visual cortical layer, the theta explosive type refers to a theta explosive type stimulation mode, and the theta explosive type refers to a theta explosive type transcranial magnetic stimulation mode. The TMS breaks through the limitation that a traditional therapy focuses on retina local repair, cortex-retina function compensation is achieved by regulating visual cortex nerve plasticity, clinical data shows that BCVA of an MMD patient can be averagely improved by 0.22 log MAR, the macular sensitivity is remarkably improved, the treatment effect on extreme myopia patients with the axial length larger than or equal to 32 mm is better, and the application prospect is wide. The treatment blank that the existing invasive therapy is taboo due to the fragile eyeball structure is filled. The non-invasive operation avoids the risk of operative complications, no adverse reaction report exists in the treatment process, the tolerance of a patient is good, the curative effect is kept stable in follow-up visit of four weeks, and repeated invasive operation is not needed.

The present application belongs to the technical field of robot intelligent control, and discloses a kind of embodied intelligent robot behavior mode self-adapting adjustment system, including neural morphological perception module, collects and fuses multimodal environment perception information, borrows from the sparse coding principle of brain visual cortex, carries out space-time compression to multimodal environment perception information, generates environment state representation vector, and constructs neural morphological perception path;Cognitive constraint decision module, based on environment state representation vector, generates action strategy using neural symbol hybrid architecture;Through cognitive momentum optimization mechanism, introduce strategy inertia term to improve the updating process of action strategy parameter, obtain behavior decision vector;Variable impedance execution module, the behavior decision vector is mapped into multiple virtual muscle synergies by muscle synergistic mapping rule, and the expected motion trajectory of each execution joint of the robot is solved;Make embodied intelligent robot have stronger adaptability, stability and execution ability.

1. Name of the product in this design: Flexible electrode for visual cortex stimulation. 2. Purpose of this design: To manufacture flexible electrodes for visual cortical stimulation. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key features: the front view. 5. This design is for a thin product; other views are omitted.

The application provides a robot positioning mapping method based on a visual cortex and hippocampus space coding, and the method comprises the following steps: acquiring linear velocity and angular velocity through a wheel encoder and an inertial measurement unit, and obtaining robot pose information through path integration; collecting scene images by using a camera and extracting GIST features, obtaining a winning cell in a view cell network through Euclidean distance matching, updating weights, and introducing a posteriori entropy adaptive threshold to perform robust scene matching; storing the pose information and the successfully matched weight vector into a hippocampus CA1 area location cell, eliminating cumulative errors through iterative optimization, controlling the map size through space density redundancy pruning, and adopting a hierarchical switching strategy to perform scale stretching optimization, so that fast mapping is realized. Through simulating a biological space coding mechanism, the application improves scene recognition robustness, positioning consistency and mapping efficiency, and is suitable for intelligent navigation of a mobile robot.

The present invention provides an object detection method and device based on convolution of the primary visual cortex. The detection method includes: obtaining an image to be detected; successively performing multiple times of feature map size compression and feature extraction based on the primary visual cortex mechanism on the image to be detected to obtain multiple backbone feature maps of different sizes; performing multiple times of convolution feature extraction and channel aggregation based on the primary visual cortex mechanism on the multiple backbone feature maps to obtain object feature maps of multiple sizes; and fusing the multiple object feature maps to obtain an object detection result. The present invention improves the problems in the prior art that the object detection method is easily interfered by noise and has poor environmental adaptability.

This invention relates to the field of artificial retina technology and provides a bionic artificial retina system, including an image acquisition module, a signal processing module, and a microneedle assembly. The image acquisition module is used to acquire images; the signal processing module is used to process the images acquired by the image acquisition module into electrical signals; the microneedle assembly is used to be implanted in the visual cortex of the human brain, receiving the electrical signals processed by the signal processing module and sending them to the visual cortex. This bionic artificial retina system of the present invention directly acquires on-site images through the image acquisition module, and then the signal processing module converts them into electrical signals that can be acquired by the microneedle assembly in real time. The microneedle assembly can then transmit the electrical signals to the visual cortex of the human brain, restoring visual perception in visually impaired organisms through electrical stimulation.

The application discloses a light adjustment method based on real-time neural safety monitoring and related equipment, and belongs to the technical field of data processing. Wherein, the method comprises: in the case of adjusting light to the user, collecting the user's retinal electrical response signal and visual cortex electrical response signal; extracting the electrical response parameter value from the retinal electrical response signal and the visual cortex electrical response signal; calculating the deviation degree value of the electrical response parameter value relative to the preset parameter value; determining the pathological waveform mode information of the functional abnormality according to the deviation degree value; according to the deviation degree value and the pathological waveform mode information, executing the hierarchical response measures, the hierarchical response measures including at least one of the following: outputting prompt information, reducing the output power of the adjustment light, suspending the light output of the adjustment light, and terminating the light output of the adjustment light.

Devices, systems, and methods for a treating dementia or Alzheimer's disease in a subject in need thereof. In one example, combined auditory and visual stimuli having a frequency of about 20 Hz to about 60 Hz, and more specifically about 40 Hz, are noninvasively delivered to the subject to induce synchronized gamma oscillations in at least one brain region of the subject. In particular, pursuant to various treatment and exposure protocols, combined auditory and visual stimulation (as opposed to auditory or visual stimulation alone) promotes a microglia response in the medial prefrontal cortex (mPFC). More generally, combined auditory and visual stimulation induces an extended microglia clustering response in the auditory cortex, the visual cortex, and the mPFC.

The application discloses a kind of visual cortex's multiscale small target detection method, device and equipment, the method includes: obtaining input image;Through the feature extraction of the input image by the preset imitated primary visual perception cortex model, obtain first feature map;The preset imitated primary visual perception cortex model includes VOneBlock layer, Conv layer and feature fusion layer;Through the target detection of the first feature map by the preset target detection model, obtain five different size target feature maps;The target classification and coordinate positioning of the five different size target feature maps are carried out, and target detection result is obtained.The application carries out target detection by five different size target feature maps, effectively improves the feature extraction capability to small target.Meanwhile join imitated primary visual perception cortex model, by simulating brain primary visual cortex perception mechanism, improve the anti-interference ability of model.

Devices, systems, and methods for a treating dementia or Alzheimer's disease in a subject in need thereof. In one example, combined auditory and visual stimuli having a frequency of about 20 Hz to about 60 Hz, and more specifically about 40 Hz, are non-invasively delivered to the subject to induce synchronized gamma oscillations in at least one brain region of the subject. In particular, pursuant to various treatment and exposure protocols, combined auditory and visual stimulation (as opposed to auditory or visual stimulation alone) promotes a microglia response in the medial prefrontal cortex (mPFC). More generally, combined auditory and visual stimulation induces an extended microglia clustering response in the auditory cortex, the visual cortex, and the mPFC.