Company patents
Zhejiang Normal University
Zhejiang Normal University exhibits a surprising, broad patent strategy, with its top two categories, Computer Vision and Material & Chemical Analysis, each representing 12.9% of its portfolio. While Material & Chemical Analysis saw a remarkable 500.0% YoY growth in 2025, its sharp decline of 83.3% so far in 2026 suggests a shifting focus, contrasting with the consistent growth in Computer Vision, which experienced a 200.0% YoY increase in 2026.
Patent Trend by Technology Area
Yearly patent publications since 2023
Product themes
Product-level themes inferred from filings since 2023, with category chips showing where each theme appears. Select a theme to filter the patents below.
62 US filings (since 2023) · 12 categories · 16 themes
Techniques for combining data from disparate sensor types (e.g., cameras, radar, mobile device signals) to achieve a more robust and comprehensive understanding of an environment or subject, often leveraging machine learning for interpretation and correlation.
Techniques for combining and analyzing information from multiple distinct data modalities (e.g., text, image, video, audio, sensor data) to derive richer insights or improve system performance and decision-making.
Algorithms and hardware optimizations for rapidly identifying and characterizing relevant visual features (e.g., objects, motion, gradients) from images or video streams, often integrating machine learning for feature representation and recognition, with a focus on real-time performance and reduced computational cost.
Processes and methodologies for the efficient and scalable preparation of complex heterocyclic compounds and their precursors, including specific reaction conditions, purification techniques, and intermediate compounds.
Engineering of artificial subwavelength structures (meta-atoms) to create metasurfaces that manipulate light properties (phase, polarization, wavelength) for multi-functional optical devices.
Development of sophisticated optical lens assemblies and computational methods to achieve high-resolution, precise, or specialized imaging, often for medical or scientific applications.
Systems leveraging artificial intelligence and machine learning to dynamically adjust educational content, learning paths, goals, or feedback based on individual user performance, progress, or physiological data. This includes generating personalized exercises, recommendations, and adaptive sequencing of knowledge points.
Methods and apparatus for detecting objects and determining their three-dimensional position and orientation (pose) using imagery or point cloud data, often for navigation, surveying, or environmental understanding.
Methods and compositions for identifying, quantifying, or characterizing specific biological molecules (e.g., nucleic acids, proteins, metabolites, antibodies) or microbial species, often for diagnostic, prognostic, or quality control applications.
Systems that employ imaging and image processing to automatically detect defects, verify states, or ensure quality control in manufactured goods, printed materials, or industrial processes.
Design and synthesis of acyclic or carbocyclic organic compounds that selectively modulate specific biological targets or pathways for the treatment of diseases.
Techniques and hardware for autonomous systems to gather and interpret data about their surroundings, including obstacle detection, object recognition, and depth estimation, to inform control decisions.
Integrating game-like mechanics, interactive challenges, and engaging user interface elements (e.g., avatars, reward systems, narrative structures) into educational or therapeutic applications to enhance user motivation, engagement, and learning retention.
Methods and apparatus for the efficient and selective production of organic compounds, including amines, acids, and esters, often involving catalytic or continuous processes and purification steps.
Techniques utilizing deep learning models like Generative Adversarial Networks (GANs) or diffusion models to create new images, modify existing ones, or generate synthetic data based on various inputs or conditions.
Methods for training machine learning models across multiple decentralized devices or servers while keeping data localized, often involving aggregation of model parameters and secure communication.
Patents
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Federated & Distributed ML