Semi-Supervised Domain Adaptation for Holistic Counting under Label Gap
This paper proposes a novel approach for semi-supervised domain adaptation for holistic regression tasks, where a DNN predicts a continuous value y∈R given an input image x. The current literature generally lacks specific domain adaptation approaches for this task, as most of them mostly focus on classification. I...
Plant phenotyping on-demand: an integrative web-based framework using drones and participatory sensing in greenhouses
In this paper, we present an empirical evaluation of 30 features used in touch-based continuous authentication. It is essential to identify the most significant features for each user, as behaviour is different amongst humans. Thus, a fixed feature set cannot be applied to all models. We highlight this...
CAPE: Context-Aware Private Embeddings for Private Language Learning
Deep learning-based language models have achieved state-of-the-art results in a number of applications including sentiment analysis, topic labelling, intent classification and others. Obtaining text representations or embeddings using these models presents the possibility of encoding personally identifiable...