Location History:
- Suwon-si, KR (2022 - 2024)
- Seoul, KR (2022 - 2024)
Company Filing History:
Years Active: 2022-2024
Title: Hyunsun Park: Innovator in Neural Network Technologies
Introduction
Hyunsun Park is a prominent inventor based in Suwon-si, South Korea. He has made significant contributions to the field of neural networks, holding a total of 10 patents. His work focuses on advancing the capabilities of neural processing technologies.
Latest Patents
One of his latest patents is a "Neural processing apparatus and method with neural network pool processing." This invention involves a processor-implemented method that includes obtaining intermediate pooling results corresponding to sub-pooling kernels. These kernels are derived from decomposing an original pooling kernel. The method performs a pooling operation on input pixels within a current window of an input feature map. It then obtains a final pooling result by post-processing the intermediate results and determines an output pixel value based on this final result.
Another notable patent is the "Method and apparatus for quantizing parameters of neural network." This method calculates a bit shift value for each parameter, indicating a degree outside a bit range of a fixed-point format. It updates the fixed-point format based on these calculated values and quantizes parameters during a learning or inference process according to the updated format.
Career Highlights
Hyunsun Park has worked with leading organizations in the technology sector, including Samsung Electronics and Seoul National University. His experience in these institutions has allowed him to develop and refine his innovative ideas in neural network technologies.
Collaborations
He has collaborated with notable colleagues such as Junhaeng Lee and Sehwan Lee, contributing to advancements in their shared field of expertise.
Conclusion
Hyunsun Park's work in neural network technologies showcases his innovative spirit and dedication to advancing the field. His patents reflect significant advancements that could shape the future of neural processing.
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