research
∙
01/21/2021
Copycat CNN: Are Random Non-Labeled Data Enough to Steal Knowledge from Black-box Models?
Convolutional neural networks have been successful lately enabling compa...
share
research
∙
11/07/2020
Deep traffic light detection by overlaying synthetic context on arbitrary natural images
Deep neural networks come as an effective solution to many problems asso...
research
∙
07/01/2020
Self-supervised Deep Reconstruction of Mixed Strip-shredded Text Documents
The reconstruction of shredded documents consists of coherently arrangin...
research
∙
03/23/2020
Fast(er) Reconstruction of Shredded Text Documents via Self-Supervised Deep Asymmetric Metric Learning
The reconstruction of shredded documents consists in arranging the piece...
research
∙
07/23/2019
Effortless Deep Training for Traffic Sign Detection Using Templates and Arbitrary Natural Images
Deep learning has been successfully applied to several problems related ...
research
∙
07/19/2019
Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night
Deep learning techniques have enabled the emergence of state-of-the-art ...
research
∙
06/04/2019
Traffic Light Recognition Using Deep Learning and Prior Maps for Autonomous Cars
Autonomous terrestrial vehicles must be capable of perceiving traffic li...
research
∙
06/15/2018
Ego-Lane Analysis System (ELAS): Dataset and Algorithms
Decreasing costs of vision sensors and advances in embedded hardware boo...
research
∙
06/14/2018
Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data
In the past few years, Convolutional Neural Networks (CNNs) have been ac...
research
∙
05/30/2018
Automatic Large-Scale Data Acquisition via Crowdsourcing for Crosswalk Classification: A Deep Learning Approach
Correctly identifying crosswalks is an essential task for the driving ac...
research
∙
06/28/2017
