20 citations · 21 across the 4 of their papers we have counts for
6 papers
Can We Teach Computers to Understand Art? Domain Adaptation for Enhancing Deep Networks Capacity to De-Abstract Art
Mihai Badea, Corneliu Florea, Laura Florea +1
Humans comprehend a natural scene at a single glance; painters and other visual artists, through their abstract representations, stressed this capacity to the limit. The performanc…
The use of deep learning in image segmentation, classification and detection
M. S. Badea, I. I. Felea, L. M. Florea +1
Recent years have shown that deep learned neural networks are a valuable tool in the field of computer vision. This paper addresses the use of two different kinds of network archit…
Pandora: Description of a Painting Database for Art Movement Recognition with Baselines and Perspectives
Corneliu Florea, Razvan Condorovici, Constantin Vertan +3
To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitiz…
Pain Intensity Estimation by a Self--Taught Selection of Histograms of Topographical Features
Corneliu Florea, Laura Florea, Raluca Boia +2
Pain assessment through observational pain scales is necessary for special categories of patients such as neonates, patients with dementia, critically ill patients, etc. The recent…
Robust Eye Centers Localization with Zero--Crossing Encoded Image Projections
Laura Florea, Corneliu Florea, Constantin Vertan
This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a Multi Layer Perceptron (MLP) classifier. The…
High Dynamic Range Imaging by Perceptual Logarithmic Exposure Merging
Corneliu Florea, Constantin Vertan, Laura Florea
In this paper we emphasize a similarity between the Logarithmic-Type Image Processing (LTIP) model and the Naka-Rushton model of the Human Visual System (HVS). LTIP is a derivation…