Company Filing History:
Years Active: 2020
Title: Haseeb Bokhari: Innovator in Convolutional Neural Network Applications
Introduction
Haseeb Bokhari is a prominent inventor based in Kingsford, Australia. He has made significant contributions to the field of technology, particularly in optimizing memory for Convolutional Neural Network (CNN) applications. With a total of 2 patents, his work focuses on enhancing the efficiency of System-on-Chip (SoC) configurations.
Latest Patents
Haseeb Bokhari's latest patents include innovative methods for scheduling operations and optimizing memory access in CNN applications. The first patent, titled "Layer-based operations scheduling to optimise memory for CNN applications," outlines a method for configuring an SoC to execute a CNN. This involves receiving scheduling schemes, selecting a scheme for the current layer, determining the current state of memory, and selecting a scheduling scheme for the next layer based on memory conditions.
The second patent, "Memory access optimisation using per-layer computational mapping and memory allocation for CNN application," details a method for determining memory access requirements and optimizing memory allocation for on-chip memory. This process aims to minimize external memory access for each CNN layer, thereby enhancing overall performance.
Career Highlights
Haseeb Bokhari is currently employed at Canon Kabushiki Kaisha, where he continues to develop innovative solutions in the field of technology. His work has garnered attention for its practical applications in improving the efficiency of CNN processes.
Collaborations
Haseeb has collaborated with notable coworkers, including Jorgen Peddersen and Sridevan Parameswaran. Their combined expertise contributes to the advancement of technology in their respective fields.
Conclusion
Haseeb Bokhari is a dedicated inventor whose work in optimizing CNN applications has the potential to significantly impact the technology landscape. His innovative patents reflect a commitment to enhancing efficiency and performance in complex systems.