Ashulekha Gupta
Papers
1
Total Citations
10
H-Index
1
About
Ashulekha Gupta is a prominent researcher at the forefront of artificial intelligence, with a primary focus on deep learning and its transformative applications in computer vision. Her work centers on harnessing the power of distributed data representations through multiple levels of abstraction, enabling machines to interpret and analyze visual information with unprecedented accuracy. Gupta’s most cited paper, "A review approach on deep learning algorithms in computer vision" (2023), has garnered 10 citations, establishing her as a key voice in synthesizing the rapidly evolving landscape of deep learning systems. This seminal review critically examines how massive data generation drives algorithmic advancements, addressing the growing challenge of data analysis in an era of information overload. Her contributions are particularly notable for bridging theoretical foundations with practical implementations, offering researchers and students a comprehensive roadmap for navigating complex neural network architectures. Gupta’s work underscores the critical role of deep learning in revolutionizing fields from autonomous systems to medical imaging, making her a vital resource for those seeking to understand the future of intelligent visual computing.
Research Focus
Key Achievements
Top Papers
- 1A review approach on deep learning algorithms in computer vision10 citations · 2023