Srishti Srivastava

Papers

Total Citations

123

H-Index

About

Srishti Srivastava is a leading researcher at the intersection of computer vision and marine science, whose work harnesses deep learning to decode the hidden world beneath the waves. Her most influential contribution, a 2022 survey on deep learning techniques for underwater image classification (123 citations), has become a foundational resource for the field, systematically mapping how neural networks can identify everything from fish and plankton to coral reefs and diver gestures. By demonstrating that automated classification is essential for measuring water body health, Srivastava has bridged the gap between artificial intelligence and critical environmental monitoring. Her work tackles the unique challenges of underwater imagery—poor visibility, color distortion, and complex lighting—pushing the boundaries of what computer vision can achieve in extreme conditions. Beyond her survey, Srivastava’s research continues to advance object detection and classification in aquatic environments, with applications ranging from biodiversity assessment to maritime security. Her contributions are shaping how researchers and conservationists use AI to understand and protect our oceans, making her a pivotal figure in the growing field of environmental computer vision.