5 papers
Rule-Based Spatial Mixture-of-Experts U-Net for Explainable Edge Detection
Bharadwaj Dogga, Kaaustaaub Shankar, Gibin Raju +2
Deep learning models like U-Net and its variants, have established state-of-the-art performance in edge detection tasks and are used by Generative AI services world-wide for their…
A Comparative Study of Adversarial Robustness in CNN and CNN-ANFIS Architectures
Kaaustaaub Shankar, Bharadwaj Dogga, Kelly Cohen
Convolutional Neural Networks (CNNs) achieve strong image classification performance but lack interpretability and are vulnerable to adversarial attacks. Neuro-fuzzy hybrids such a…
Fuzzy Decisions on Fluid Instabilities: Autoencoder-Based Reconstruction meets Rule-Based Anomaly Classification
Bharadwaj Dogga, Gibin Raju, Wilhelm Louw +1
Shockwave classification in shadowgraph imaging is challenging due to limited labeled data and complex flow structures. This study presents a hybrid framework that combines unsuper…
Fuzzy-RRT for Obstacle Avoidance in a 2-DOF Semi-Autonomous Surgical Robotic Arm
Kaaustaaub Shankar, Wilhelm Louw, Bharadwaj Dogga +3
AI-driven semi-autonomous robotic surgery is essential for addressing the medical challenges of long-duration interplanetary missions, where limited crew sizes and communication de…
A model agnostic eXplainable AI based fuzzy framework for sensor constrained Aerospace maintenance applications
Bharadwaj Dogga, Anoop Sathyan, Kelly Cohen
Machine Learning methods have extensively evolved to support industrial big data methods and their corresponding need in gas turbine maintenance and prognostics. However, most unsu…