San Francisco, CA, United States of America

Daniel Havír


Average Co-Inventor Count = 8.0

ph-index = 1

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: The Innovations of Daniel Havír: A Pioneer in Semantic Segmentation

Introduction

Daniel Havír, an innovative inventor based in San Francisco, California, has made significant strides in the field of machine learning. His groundbreaking patent focuses on enhancing the efficiency of labeling tasks through advanced semantic segmentation techniques. This invention showcases his dedication to pushing the boundaries of technology and improving user experience in data annotation.

Latest Patents

Daniel is the proud inventor of a singular yet impactful patent titled "Prelabeling for Semantic Segmentation Tasks." This patent outlines a sophisticated technique for generating a multi-scale representation of an image, which serves as input for a machine learning model. By performing operations that yield a semantic segmentation, the model predicts labels for various pixel regions in the image. Moreover, the technique includes a user interface that assists users in specifying these labels more effectively, which can be tremendously beneficial for applications in computer vision and artificial intelligence.

Career Highlights

Currently, Daniel Havír is associated with Scale AI, Inc., a company renowned for its cutting-edge solutions in data annotation and machine learning. His role at the company allows him to apply his innovative ideas directly to real-world challenges, contributing to advancements within the field. With one patent under his name, Daniel has already established himself as a key figure in the technological landscape.

Collaborations

Throughout his career, Daniel has collaborated with talented individuals such as Chiao-Lun Cheng and Elliot Branson. These partnerships have fostered an environment of creativity and innovation, allowing them to collectively push the frontiers of machine learning and data processing techniques.

Conclusion

Daniel Havír's contributions to semantic segmentation are paving the way for more efficient and effective machine learning applications. His patent not only highlights his inventive prowess but also signifies the importance of collaboration in driving technological advancements. As he continues his work at Scale AI, Inc., the future looks bright for further innovations stemming from his expertise.

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