5 papers
Semantically-Guided Domain Randomization for Industrial Object Detection in Low-Image-Budget Regimes
Jose Moises Araya-Martinez, Gautham Mohan, Jens Lambrecht
Retraining visual perception pipelines in High-Mix, Low-Volume (HMLV) automotive manufacturing must be carried out under tight annotation, energy, and time budgets, yet most Synthe…
Adapting Vision-Language Models for Human-Readable XAI in Industrial Object Detection
Sarvenaz Sardari, Freddy Fernandes, Samarth Yelvande +2
Explainable Artificial Intelligence (XAI) solutions are essential for building trust in AI technologies and their integration in real manufacturing lines. However, most existing me…
SynthRender and I-AsSET: Open-Source Framework and Dataset for Bidirectional Sim-Real Transfer in Industrial Object Perception
Jose Moises Araya-Martinez, Thushar Tom, Adrián Sanchis Reig +3
Object perception is fundamental for tasks such as robotic material handling and quality inspection. However, modern supervised deep-learning models require large annotated dataset…
Synthetic Industrial Object Detection: GenAI vs. Feature-Based Methods
Jose Moises Araya-Martinez, Adrián Sanchis Reig, Gautham Mohan +3
Reducing the burden of data generation and annotation remains a major challenge for the cost-effective deployment of machine learning in industrial and robotics settings. While syn…
Zero-Shot Multi-Criteria Visual Quality Inspection for Semi-Controlled Industrial Environments via Real-Time 3D Digital Twin Simulation
Jose Moises Araya-Martinez, Gautham Mohan, Kenichi Hayakawa Bolaños +4
Early-stage visual quality inspection is vital for achieving Zero-Defect Manufacturing and minimizing production waste in modern industrial environments. However, the complexity of…