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San Jose, CA, United States of America

Perceive Corporation

USPTO Granted Patents = 83

Forward Citations = 465

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11 inventors (with patents filed for the assignee):

Steven L Teig (77 out of 461 patents)

Jung Ko (28 out of 48 patents)

Kenneth Duong (28 out of 54 patents)

4. Eric A Sather (26 out of 46 patents)

5. Andrew C Mihal (17 out of 25 patents)

6. Ilyas Mohammed (6 out of 285 patents)

7. Brian Thomas (4 out of 9 patents)

8. Alexandru F Drimbarean (3 out of 3 patents)

9. Ryan J Cassidy (2 out of 3 patents)

10. Justin Tantiongloc (1 out of 2 patents)

11. Won Rhee (1 out of 4 patents)

Core Competencies:

Neural Network

Optimization

Quantization

Error Minimization

Machine Learning

Training Techniques

Dynamic Memory

Sparsity

Input Buffering

Depth Perception

Context-Sensitive Detection

Compressive Sensing

83 patents: Sort by Forward Citations

1. 12159214 - Buffering of neural network inputs and outputs (2024-12-03),

2. 12136039 - Optimizing global sparsity for neural network (2024-11-05),

3. 12124939 - Generation of machine-trained network instructions (2024-10-22),

4. 12118463 - Weight value decoder of neural network inference circuit (2024-10-15),

5. 12112254 - Optimizing loss function during training of network (2024-10-08),

6. 12093816 - Initialization of values for training a neural network with quantized weights (2024-09-17),

7. 12093696 - Bus for transporting output values of a neural network layer to cores specified by configuration data (2024-09-17),

8. 12061988 - Decomposition of ternary weight tensors (2024-08-13),

9. 12061981 - Decomposition of weight tensors in network with value quantization (2024-08-13),

10. 12051000 - Training network to minimize worst-case error (2024-07-30),

11. 12045725 - Batch normalization for replicated layers of neural network (2024-07-23),

12. 12008465 - Dynamic generation of data sets for training machine-trained network (2024-06-11),

13. 12001948 - Machine trained network using novel coding techniques (2024-06-04),

14. 11995555 - Training a neural network with quantized weights (2024-05-28),

15. 11995537 - Training network with batches of input instances (2024-05-28),

Company Overview

Perceive Corporation, based in San Jose, CA, specializes in advanced neural network optimization technologies. The company focuses on enhancing machine learning capabilities through innovative techniques such as quantization, error minimization, and dynamic memory management. By leveraging sparsity and efficient training methods, Perceive aims to improve the performance and efficiency of neural networks, making them more accessible for a variety of applications across industries. Their research contributes significantly to the evolving landscape of artificial intelligence.

Profile summary synthesized from public USPTO records and patent filings.

Company Badge

USPTO Data Jan 1 1976 - Oct 20 2026

83 Patents

#130 in San Jose, CA

#1,036 in California

#4,473 in US

#9,158 in the World

San Jose, CA, United States of America

Perceive Corporation

Forward Citations = 465

11 inventors:

Steven L Teig (77 out of 461 patents)

Jung Ko (28 out of 48 patents)

Kenneth Duong (28 out of 54 patents)

4. Eric A Sather (26 out of 46 patents)

5. Andrew C Mihal (17 out of 25 patents)

IDiyas Innovation Intelligence. (2026). Company Patent Portfolio: Perceive Corporation. Retrieved from https://idiyas.com/company/perceive

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

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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