Boston, MA, United States of America

Kushal Kafle

USPTO Granted Patents = 5 

Average Co-Inventor Count = 5.3

ph-index = 1


Company Filing History:


Years Active: 2024-2025

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5 patents (USPTO):

Title: Innovations of Kushal Kafle

Introduction

Kushal Kafle is a prominent inventor based in Boston, MA, known for his contributions to the field of image processing and color prediction. With a total of four patents to his name, Kafle has made significant strides in developing systems that enhance the understanding and manipulation of digital images.

Latest Patents

Kafle's latest patents include "Systems and methods for predicting long-tail colors in images." This invention describes methods for generating a color vector from an image, which includes an object with a specific color. The system utilizes a color classification network to create a bias vector that helps in generating an unbiased color vector, ultimately indicating the object's color. Another notable patent is "Extracting attributes from arbitrary digital images utilizing a multi-attribute contrastive classification neural network." This patent outlines a system that employs a multi-attribute contrastive classification neural network to extract multiple attributes from objects in digital images. The system includes various neural networks designed to enhance the accuracy of attribute extraction.

Career Highlights

Kafle is currently employed at Adobe, Inc., where he continues to innovate and develop cutting-edge technologies in image processing. His work at Adobe has allowed him to collaborate with other talented professionals in the field, further enhancing his contributions to technology.

Collaborations

Some of Kafle's notable coworkers include Trung Huu Bui and Franck Dernoncourt. Their collaborative efforts have likely contributed to the success of various projects within Adobe.

Conclusion

Kushal Kafle's work in image processing and color prediction showcases his innovative spirit and dedication to advancing technology. His patents reflect a deep understanding of complex systems and a commitment to improving how we interact with digital images.

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