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Found 6 papers, 0 papers with code
Margin-Mix: Semi–Supervised Learning for Face Expression Recognition
In this paper, as we aim to construct a semi-supervised learning algorithm, we exploit the characteristics of the Deep Convolutional Networks to provide, for an input image, both an embedding descriptor and a prediction.
Can We Teach Computers to Understand Art? Domain Adaptation for Enhancing Deep Networks Capacity to De-Abstract Art
In the next level of evaluation, we identify aspects that hinder the CNNs' recognition, such as artistic abstraction.
Pandora: Description of a Painting Database for Art Movement Recognition with Baselines and Perspectives
Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images, we propose a novel large scale dataset of digital paintings.
Pain Intensity Estimation by a Self--Taught Selection of Histograms of Topographical Features
Pain assessment through observational pain scales is necessary for special categories of patients such as neonates, patients with dementia, critically ill patients, etc.
Robust Eye Centers Localization with Zero--Crossing Encoded Image Projections
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.
High Dynamic Range Imaging by Perceptual Logarithmic Exposure Merging
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).
