68 citations · 76 across the 26 of their papers we have counts for
8 papers · 1 filter
One Patch is All You Need: Joint Surface Material Reconstruction and Classification from Minimal Visual Cues
Sindhuja Penchala, Gavin Money, Gabriel Marques +5
Understanding material surfaces from sparse visual cues is critical for applications in robotics, simulation, and material perception. However, most existing methods rely on dense…
Towards Neurocognitive-Inspired Intelligence: From AI's Structural Mimicry to Human-Like Functional Cognition
Noorbakhsh Amiri Golilarz, Hassan S. Al Khatib, Shahram Rahimi
Artificial intelligence has advanced significantly through deep learning, reinforcement learning, and large language and vision models. However, these systems often remain task spe…
Surformer v2: A Multimodal Classifier for Surface Understanding from Touch and Vision
Manish Kansana, Sindhuja Penchala, Shahram Rahimi +1
Multimodal surface material classification plays a critical role in advancing tactile perception for robotic manipulation and interaction. In this paper, we present Surformer v2, a…
Estimating Reliability of Electric Vehicle Charging Ecosystem using the Principle of Maximum Entropy
Himanshu Tripathi, Subash Neupane, Shahram Rahimi +3
This paper addresses the critical challenge of estimating the reliability of an Electric Vehicle (EV) charging systems when facing risks such as overheating, unpredictable, weather…
Surformer v1: Transformer-Based Surface Classification Using Tactile and Vision Features
Manish Kansana, Elias Hossain, Shahram Rahimi +1
Surface material recognition is a key component in robotic perception and physical interaction, particularly when leveraging both tactile and visual sensory inputs. In this work, w…
Learning in Focus: Detecting Behavioral and Collaborative Engagement Using Vision Transformers
Sindhuja Penchala, Saketh Reddy Kontham, Prachi Bhattacharjee +7
In early childhood education, accurately detecting collaborative and behavioral engagement is essential to foster meaningful learning experiences. This paper presents an AI driven…
Towards Secure MLOps: Surveying Attacks, Mitigation Strategies, and Research Challenges
Raj Patel, Himanshu Tripathi, Jasper Stone +4
The rapid adoption of machine learning (ML) technologies has driven organizations across diverse sectors to seek efficient and reliable methods to accelerate model development-to-d…
Edge-Based Learning for Improved Classification Under Adversarial Noise
Manish Kansana, Keyan Alexander Rahimi, Elias Hossain +2
Adversarial noise introduces small perturbations in images, misleading deep learning models into misclassification and significantly impacting recognition accuracy. In this study,…