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For the Inventor, By the Inventor

Maharashtra, India

Vinayak Jayaram Pore

USPTO Granted Patents = 16 

Average Co-Inventor Count = 3.4

ph-index = 4

Forward Citations = 37(Granted Patents)


Location History:

  • Pune, IN (2010 - 2024)
  • Maharashtra, IN (2016 - 2024)

Company Filing History:

goldMedal16 out of 5,406 
 
Nvidia Corporation
 patents

Years Active: 2010-2025

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16 patents (USPTO):Explore Patents
1. 12206845 - Entropy-based pre-filtering using neural networks for streaming applications (2025-01-21),
2. 12149708 - Machine learning of encoding parameters for a network using a video encoder (2024-11-19),
3. 11875478 - Dynamic image smoothing based on network conditions (2024-01-16),
4. 11871011 - Efficient lossless compression of captured raw image information systems and methods (2024-01-09),
5. 11212539 - Efficient lossless compression of captured raw image information systems and methods (2021-12-28),
6. 11102516 - Quality aware error concealment method for video and game streaming and a viewing device employing the same (2021-08-24),
7. 9247179 - Reverse video playback in a data processing device (2016-01-26),
8. 8830341 - Selection of an optimum image in burst mode in a digital camera (2014-09-09),
9. 8787445 - Allocation of available bits to represent different portions of video frames captured in a sequence (2014-07-22),
10. 8723969 - Compensating for undesirable camera shakes during video capture (2014-05-13),
11. 8442111 - Optimal power usage in encoding data streams (2013-05-14),
12. 8351776 - Auto-focus technique in an image capture device (2013-01-08),
13. 8340512 - Auto focus technique in an image capture device (2012-12-25),
14. 8311127 - Method and apparatus to check for wrongly decoded macroblocks in streaming multimedia applications (2012-11-13),
15. 8290357 - Auto-exposure technique in a camera (2012-10-16),

Title: Vinayak Jayaram Pore: Innovator in Neural Network Applications

Introduction

Vinayak Jayaram Pore is an accomplished inventor based in Maharashtra, India, known for his innovative contributions to advancements in neural network applications. With an impressive portfolio of 16 patents, he demonstrates a strong commitment to harnessing technology for enhancing digital experiences.

Latest Patents

Among his latest patents, Vinayak has developed an "Entropy-based pre-filtering using neural networks for streaming applications." This invention utilizes a deep neural network (DNN) to optimize content streaming by adapting scene complexity based on the network conditions of an end-user device. By pre-filtering frames, the neural network reduces complexity allowing for smoother streaming without adjustments in resolution, thus improving user experience.

Another notable patent is focused on "Machine learning of encoding parameters for a network using a video encoder." This approach involves utilizing machine learning models to predict encoding parameter values based on feedback collected from the streaming video. The learning mechanism adapts and improves through reinforcement learning, using actual encoded parameters to enhance video data transmission over networks.

Career Highlights

Vinayak is currently employed at Nvidia Corporation, a company renowned for its cutting-edge technology in graphics processing and AI. His work at Nvidia embodies the intersection of innovation and practical application, showcasing his dedication to improving the efficiency of digital content delivery.

Collaborations

In his professional journey, Vinayak has collaborated with noteworthy individuals like Soumenkumar Dey and Shashank Garg. These collaborations highlight the importance of teamwork in achieving significant technological advancements and innovations in the industry.

Conclusion

Vinayak Jayaram Pore stands out as a pivotal figure in the realm of neural network technologies, demonstrating how innovation can lead to enhanced user experiences in content streaming. His contributions reflect the spirit of inventive thinking, exemplifying the vital role of inventors in shaping the future of technology.

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