Bengaluru, India

Snigdha Samal

USPTO Granted Patents = 3 

Average Co-Inventor Count = 4.5

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2024-2026

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3 patents (USPTO):Explore Patents

Title: Snigdha Samal: Innovator in Image Data Annotation

Introduction

Snigdha Samal is a prominent inventor based in Karnataka, India. She has made significant contributions to the field of data collection and model training, particularly in image data annotation. Her innovative work has the potential to enhance the efficiency and accuracy of image processing technologies.

Latest Patents

Snigdha holds a patent for an "Image data annotation and model training platform." This platform is designed for data collection, specifically focusing on image collection and model building. The patent describes a system where received media content data, including image data, can be assigned a context category. One or more context-specific models are utilized to automatically annotate the images. The platform also includes features for accuracy monitoring of image annotations, which may indicate the need for manual annotation for subsequent training. Additionally, a priority can be assigned to images, allowing them to be queued for further annotation, which can be used for model retraining. In some cases, a separate classification model is employed to identify a context category for image data from predetermined contexts.

Career Highlights

Snigdha is currently employed at Target Brands, Inc., where she continues to develop her innovative ideas and contribute to advancements in technology. Her work is characterized by a commitment to improving data annotation processes and enhancing machine learning models.

Collaborations

Snigdha collaborates with talented individuals such as Arun Patil and Mohit Sethi, who contribute to her projects and help bring her innovative ideas to fruition.

Conclusion

Snigdha Samal is a trailblazer in the field of image data annotation, with a patent that showcases her innovative approach to data collection and model training. Her contributions are paving the way for advancements in technology and improving the efficiency of image processing systems.

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