Browsing by Subject "Convolutional neural networks"
Now showing items 1-7 of 7
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Aesthetic Image Captioning from Weakly-Labelled Photographs
(2019)Aesthetic image captioning (AIC) refers to the multimodal task of generating critical textual feedbacks for photographs. While in natural image captioning (NIC), deep models are trained in an end-to-end manner using ... -
AlphaGAN: Generative adversarial networks for natural image matting
(2018)We present the first generative adversarial network (GAN) for natural image matting. Our novel generator network is trained to predict visually appealing alphas with the addition of the adversarial loss from the discriminator ... -
Class-specific Object Pose Estimation and Reconstruction using 3D Part Geometry
(2016)We propose a novel approach for detecting and reconstructing class-specific objects from 2D images. Reconstruction and detection, despite major advances, are still wanting in performance. Hence, approaches that try to solve ... -
Deep Convolutional Neural Networks for estimating lens distortion parameters
(2019)In this paper we present a convolutional neural network (CNN) to predict multiple lens distortion parameters from a single input image. Unlike other methods, our network is suitable to create high resolution output as ... -
Drone image segmentation using machine and deep learning for mapping Irish bog vegetation communities
(2020)The application of drones has recently revolutionised the mapping of wetlands due to their high spatial resolution and the flexibility in capturing images. In this study, the drone imagery was used to map key vegetation ... -
A Geometry-Sensitive Approach for Photographic Style Classification
(2018)Photographs are characterized by different compositional attributes like the Rule of Thirds, depth of field, vanishing-lines etc. The presence or absence of one or more of these attributes contributes to the overall ... -
Recognising the fine-grained actions of a goal-directed activity from multi-modal images
(Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2021)The ability to understand and respond to human activities can form the basis of many pervasive computing applications. Recognising the constituent actions of an activity can lead to a more detailed understanding of the ...