This inventor holds 2 USPTO granted patents. Top assignee: Deere & Company. Active years: 2026.
Company Filing History:
Years Active: 2026
Title: Innovations in Agricultural Technology by Inventor Ngozi Kanu
Introduction
Ngozi Kanu is an innovative inventor based in Pleasanton, CA (US). He has made significant contributions to the field of agricultural technology, particularly through his work on machine learning models integrated with agricultural knowledge graphs. His research aims to enhance the efficiency and accuracy of phenotypic inferences in agriculture.
Latest Patents
Ngozi Kanu holds a patent for "Hierarchal phenotyping using graphs." This patent describes implementations for integrating phenotyping machine learning (ML) models with an agricultural knowledge graph (AKG). The technology facilitates streamlined and flexible phenotypic inferences by traversing the AKG based on input, such as images of crops growing in an agricultural plot. The AKG includes a phenotypic taxonomy of nodes that represent a taxonomic hierarchy of organisms. The destination node corresponds to a level of the phenotypic taxonomy that aligns with the input. The phenotyping ML models are trained to generate phenotypic inferences at a specificity that corresponds to the level of the phenotypic taxonomy. The crop images are processed using the phenotyping ML model accessible via the destination node to generate valuable insights about the agricultural plot. Ngozi Kanu has 1 patent to his name.
Career Highlights
Ngozi Kanu is currently employed at Deere & Company, where he continues to develop innovative solutions in agricultural technology. His work focuses on leveraging advanced technologies to improve agricultural practices and outcomes.
Collaborations
Some of his notable coworkers include Chunfeng Wen and Chen Cao, who contribute to the collaborative efforts in research and development at Deere & Company.
Conclusion
Ngozi Kanu's contributions to agricultural technology through his innovative patent demonstrate the potential of integrating machine learning with agricultural knowledge. His work is paving the way for more efficient agricultural practices and improved crop management.