Hamed Sadeghi

Title: Hamed Sadeghi: Innovator in Machine Learning and Surveillance Technologies

Introduction

Hamed Sadeghi is a prominent inventor based in Toronto, Canada. He has made significant contributions to the fields of machine learning and surveillance technologies. With a total of 3 patents, Sadeghi's work focuses on optimizing complex systems for better efficiency and accuracy.

Latest Patents

One of Hamed Sadeghi's latest patents is titled "Regularization of recurrent machine-learned architectures with encoder, decoder, and prior distribution." This innovative modeling system trains a recurrent machine-learned model by determining a latent distribution and a prior distribution for a latent state. The parameters of the model are trained based on a divergence loss that penalizes significant deviations between the latent distribution and the prior distribution. The latent distribution for a current observation is a distribution for the latent state given a value of the current observation and the latent state for the previous observation. The prior distribution for a current observation is a distribution for the latent state given the latent state for the previous observation, independent of the value of the current observation, and represents a belief about the latent state before input evidence is taken into account.

Another notable patent is "Optimal camera selection in array of monitoring cameras." This technology automatically optimizes the efficiency of camera placement, numbers, and resolution in multi-camera monitoring and surveillance applications. In some examples, a fraction of a total area may be monitored at a higher resolution than the rest. Employing techniques such as the combinatorial state Viterbi technique or combinatorial state trellis technique, a minimum number of cameras that provide the necessary coverage at the needed resolution may be selected. This innovation allows for tracking subjects of interest in public areas, where specific cameras can image a subject's face at a higher resolution than the background.

Career Highlights

Hamed Sadeghi has worked with notable institutions such as McMaster University and The Toronto-Dominion Bank. His experience in these organizations has allowed him to develop and refine his innovative ideas in machine learning and surveillance technologies.

Collaborations

Throughout his career, Sadeghi has collaborated with talented individuals, including Shahram Shirani and Shadrokh Samavi. These collaborations have contributed to the advancement of his research and inventions.

Conclusion

Hamed Sadeghi is a distinguished inventor whose work in machine learning and