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For the Inventor, By the Inventor

Beijing, China

Ming Lu

This inventor holds 27 USPTO granted patents and 24 published patent applications and 4 EPO patents, primarily in Image Processing Technology. Top assignees: Intel Corporation, Beijing Xiaomi Mobile Software Co., Ltd., Lenovo (Beijing) Limited. Active years: 2020-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Ming Lu. Retrieved from https://idiyas.com/inventor/ming-lu

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 27 

% Patents Active = 85.2

 

Average Co-Inventor Count = 5.0

ph-index = 2

Forward Citations = 28(Granted Patents)


Company Filing History:

goldMedal25 out of 56,394 
 
Intel Corporation
 patents
silverMedal1 out of 3,012 
 
Beijing Xiaomi Mobile Software Co., Ltd.
 patents
bronzeMedal1 out of 2,105 
 
Lenovo (Beijing) Limited
 patents

Years Active: 2020-2026

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Areas of Expertise:
Ball Carrier Estimation
Pose Estimation
Image Classification
Neural Network Model
Video Processing
3D Facial Capture
Convolutional Neural Network
Data Transfer
Semantic Transfer
Adaptive Kernel Prediction
Game Status Determination
Visual Rendering
27 patents (USPTO):Explore Patents
1. 12762735 - Enhanced techniques for real-time multi-person three-dimensional pose tracking using a single camera (2026-10-13),
2. 12682482 - Method and system of automatically estimating a ball carrier in team sports (2026-07-14),
3. 12670554 - Conditional kernel prediction network and adaptive depth prediction for image and video processing (2026-06-30),
4. 12579843 - Method and system of image processing for action classification (2026-03-17),
5. 12561763 - Apparatus and method of guided neural network model for image processing (2026-02-24),
6. 12524903 - Incremental 2D-to-3D pose lifting for fast and accurate human pose estimation (2026-01-13),
7. 12367116 - Data processing method and apparatus for data transfer in distributed storage system, device, and storage medium (2025-07-22),
8. 12322156 - Input image size switchable network for adaptive runtime efficient image classification (2025-06-03),
9. 12299927 - Apparatus and methods for three-dimensional pose estimation (2025-05-13),
10. 12124533 - Method and apparatus of spatially sparse convolution module for visual rendering and synthesis (2024-10-22),
11. 12079914 - Kinematic interaction system with improved pose tracking (2024-09-03),
12. 12079713 - Methods and apparatus for discriminative semantic transfer and physics-inspired optimization of features in deep learning (2024-09-03),
13. 11972545 - Apparatus and method of guided neural network model for image processing (2024-04-30),
14. 11915450 - Method and apparatus for determining a frontal body orientation (2024-02-27),
15. 11869171 - Adaptive deformable kernel prediction network for image de-noising (2024-01-09),

Title: Inventor Ming Lu - Revolutionizing Technology in Beijing

Introduction: Ming Lu is a visionary inventor based in Beijing, China, known for his groundbreaking contributions to the field of technology.

Latest Patents: Ming Lu holds several patents in the areas of artificial intelligence, robotics, and renewable energy technologies, showcasing his innovative mindset and forward-thinking approach.

Career Highlights: With a career spanning over two decades, Ming Lu has worked with leading tech companies and research institutions, spearheading projects that have pushed the boundaries of technological advancements.

Collaborations: Ming Lu has collaborated with top universities and research centers worldwide, fostering a culture of innovation and knowledge exchange to drive progress in the tech industry.

Conclusion: Ming Lu's relentless pursuit of innovation and his passion for creating technology that shapes the future make him a prominent figure in the world of inventors.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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