8 results about "Attention focus" patented technology

The application discloses a subject-driven personalized generation method based on decoupled mask prompt attention fine-tuning, and belongs to the field of deep learning, computer vision and artificial intelligence generated content. A mask prompt decoupling module is designed to decompose the unified text prompt into a text prompt containing only the subject and a text prompt containing only the context. A subject attention focusing module and a context attention adjusting module are introduced, and independent subject feature extraction paths and context semantic adaptation paths are established, respectively. The subject identity learning and the context scene modeling are explicitly separated, and the double constraint loss guided by the mask is used for joint optimization to further prevent feature coupling. Finally, the algorithm effectively preserves the fine appearance features of the subject, significantly enhances the adaptability of the model to novel context instructions, and effectively improves the quality of personalized generation and the flexibility of context editing.

The application provides a kind of intelligent structured medical record generation method and system based on multimodal doctor-patient interaction, which comprises: real-time acquisition of dialogue voice and transcription into text sequence, while recognizing visual attention entity by listening to mouse operation in electronic medical record system.Based on the history of visual attention entity and text sequence, a logical demonstration track is constructed, and an implicit reward function is derived from it using a reverse reinforcement learning algorithm. Use the function to calculate the action reward value of each combination of visual attention entity and dialogue text, select the highest value combination as the optimal alignment strategy to determine the timing causal relationship. Map the entity and text to the medical knowledge graph, extract the shortest semantic path as the implicit clinical reasoning chain, and generate structured electronic medical record. The application deduces the diagnosis and treatment decision logic from the doctor's multimodal behavior through reverse reinforcement learning, solving the technical problem that traditional methods cannot establish the internal causal relationship between the doctor's visual attention focus and spoken content.

This invention discloses an adaptive adjustment method and system for a virtual environment, relating to the field of virtual reality technology. The method includes: performing background subtraction processing on a target image sequence when a user is experiencing a virtual environment; extracting detailed features from the target image sequence, and identifying key points using target anchor boxes based on the detailed feature information; determining the coordinates of three-dimensional key points based on the target key point information for user action behavior analysis; extracting a user eye image sequence from the target image sequence to determine eyeball image information, and analyzing the gaze direction based on the eyeball image information; analyzing the user's attention focus using image brightness distribution based on the gaze direction information; and adjusting elements of the virtual environment based on the user's action behavior information and user attention focus information. This invention enables more fine-grained virtual environment adjustment, improving the quality and naturalness of the user's immersive experience in the virtual environment.

The application discloses a method, device and electronic equipment for obtaining attention information of an object, the method comprising: displaying a stereoscopic virtual image in a virtual scene, the stereoscopic virtual image being a stereoscopic image corresponding to a virtual object in the virtual scene, the virtual object being a physical object; determining a target object in the stereoscopic virtual image, the target object being present in a display area; and determining an attention focus object in the stereoscopic virtual image based on the target object, the attention focus object belonging to at least part of the stereoscopic virtual image. The application can accurately obtain attention information of a user for a product or other physical object.

The application provides a learning guidance method and device, electronic equipment and a storage medium, relates to the technical field of computers, and is used for improving the flexibility of learning guidance and thus improving learning efficiency. The method comprises the following steps: acquiring learning data of a user and a task type currently practiced by the user in the case that the electronic equipment is in a language learning mode, wherein the learning data is used for indicating the current learning state of the user; and outputting a voice prompt according to the task type and the learning data, wherein the task type is one of animation watching, follow-up reading or interactive practice, and the voice prompt is related to an attention focus corresponding to the task type and the current learning state of the user.

The application belongs to the technical field of time prediction, and particularly relates to a time prediction method and device based on different channel attention focusing mechanisms. A scaled household electricity time sequence data vector is input into an MLP to obtain a processed output vector, and a stationary wavelet transform is performed on the output vector; based on high-frequency detail components, Granger causality analysis is performed, inverse Granger transformation is performed on the high-frequency detail components, and reconstructed household electricity time sequence data is obtained; based on low-frequency components and medium-frequency components, the correlation between different channel attentions is calculated, and multiple channels with the strongest dependency are screened; self-attention coupling is used for the channels with strong dependency, and geometric self-attention coupling is used for the channels with weak dependency; the outputs of the self-attention and the geometric self-attention are fused to obtain comprehensive features; the reconstructed frequency domain sequence data and the comprehensive features are inversely transformed again, and a final prediction result is obtained through an FFN.

The application relates to the technical field of network marketing, in particular to an online marketing promotion system and method based on the Internet, which comprises the following steps: real-time monitoring of a first interaction behavior sequence of a user on a browsing interface, wherein the first interaction behavior sequence comprises a cursor moving track, a page scrolling speed and a scrolling direction; prediction of a current attention focus area and a potential migration path of the attention focus of the user through a predefined attention model based on the first interaction behavior sequence; selection of adapted target advertisement content from an advertisement library based on the potential migration path, and control of the target advertisement content to appear at a preset position on the potential migration path. Through the current focus area position and the historical scrolling direction, candidate content blocks that the user may pay attention to next are predicted, and a visual path between the two is taken as a core basis for advertisement delivery, so that the advertisement can be arranged on the path in advance in the process of natural migration of the user's attention, and the effective reach rate of the advertisement is improved.

This invention relates to the field of intelligent educational interaction and discloses an adaptive cognitive guidance method for children's microscopes based on multimodal perception. The method includes: real-time acquisition of sample image sequences and user operation time-series data; extraction of semantic features through image understanding, generation of a spatial attention map through behavioral analysis, and fusion of the two to obtain a feature vector; inputting the feature vector of a continuous time window into a cognitive state inference model, outputting cognitive state labels containing attention focus, exploration intention, and confusion level; based on the target category corresponding to the intention and focus, retrieving popular science materials from a knowledge graph, and dynamically assembling them by a multimodal generator according to the guidance state machine logic into guidance content including highlighted annotations, voice narration, and animation, which is then rendered and presented in real time. This invention achieves intelligent understanding and personalized guidance of children's observation intentions, transforming one-way observation into interactive inquiry-based learning, improving cognitive conversion efficiency and the scientific enlightenment experience.