29 citations · 94 across the 14 of their papers we have counts for
4 papers · 1 filter
Controllable Image Synthesis of Industrial Data Using Stable Diffusion
Gabriele Valvano, Antonino Agostino, Giovanni De Magistris +2
Training supervised deep neural networks that perform defect detection and segmentation requires large-scale fully-annotated datasets, which can be hard or even impossible to obtai…
Transfer Learning From Synthetic To Real Images Using Variational Autoencoders For Precise Position Detection
Tadanobu Inoue, Subhajit Chaudhury, Giovanni De Magistris +1
Capturing and labeling camera images in the real world is an expensive task, whereas synthesizing labeled images in a simulation environment is easy for collecting large-scale imag…
Focusing on What is Relevant: Time-Series Learning and Understanding using Attention
Phongtharin Vinayavekhin, Subhajit Chaudhury, Asim Munawar +4
This paper is a contribution towards interpretability of the deep learning models in different applications of time-series. We propose a temporal attention layer that is capable of…
Limiting the Reconstruction Capability of Generative Neural Network using Negative Learning
Asim Munawar, Phongtharin Vinayavekhin, Giovanni De Magistris
Generative models are widely used for unsupervised learning with various applications, including data compression and signal restoration. Training methods for such systems focus on…