Ian Kenneth Stadler

Title: Ian Kenneth Stadler: Innovator in Embedded Artificial Neural Networks

Introduction

Ian Kenneth Stadler is a prominent inventor based in Richmond, CA. He has made significant contributions to the field of artificial intelligence, particularly in the area of embedded artificial neural networks. With a total of 2 patents, Stadler's work focuses on enhancing the performance and verification of these advanced systems.

Latest Patents

Stadler's latest patents include "Verification of Embedded Artificial Neural Networks Systems and Methods" and "Deep Learning Inference Systems and Methods for Imaging Systems." The first patent discloses various techniques for automated verification of the performance of embedded artificial neural networks (ANNs). This method involves converting a reference ANN to generate an embedded ANN for deployment on an imaging device. It also includes processing predetermined images to generate inference results and comparing these results to evaluate the performance of the embedded ANN.

The second patent focuses on deep learning inference for imaging systems. It describes an imaging device that processes images through a trained inference network to determine inference results. The host system trains a neural network for image classification and transmits the trained inference network to the imaging device, enabling stand-alone image classification and object detection.

Career Highlights

Ian Kenneth Stadler is currently employed at Teledyne FLIR Commercial Systems, Inc., where he continues to innovate in the field of imaging and artificial intelligence. His work has been instrumental in advancing the capabilities of imaging devices through the integration of deep learning technologies.

Collaborations

Stadler has collaborated with notable colleagues such as Shuen Yan Stephen Se and Damian Michael Patrick Nesbitt. These collaborations have further enriched his research and development efforts in the field of artificial intelligence.

Conclusion

Ian Kenneth Stadler is a key figure in the development of embedded artificial neural networks, with a focus on enhancing their performance and verification. His contributions through patents and collaborations continue to shape the future of imaging systems and artificial intelligence.