Indira Bidari

Papers

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About

Indira Bidari’s research lies at the intersection of computer vision and deep learning, with a primary focus on indoor scene recognition and object detection. Her most-cited work, “Deep learning framework for scene based indoor location recognition” (2017, 9 citations), addresses a critical challenge in robotics and human-computer interaction: enabling machines to accurately interpret and navigate complex indoor environments. By leveraging deep neural networks, Bidari’s framework enhances a robot’s ability to discern interior spaces, such as rooms or corridors, which is essential for autonomous navigation and human-robot collaboration. This contribution is particularly relevant as mobile robotics and drone technology mature, yet still struggle with fine-grained environmental understanding. Bidari’s work bridges this gap, offering a scalable solution for real-world applications like assistive robotics and smart building systems. Her research underscores the importance of context-aware AI, where machines not only detect objects but also comprehend their spatial and functional settings. With 9 citations, her paper has laid groundwork for subsequent studies in indoor localization, reflecting her impact on advancing scene-level perception for interactive robotics.