Results 1 to 10 of about 21,106 (37)
Language Models for Image Captioning: The Quirks and What Works [PDF]
, 2015 Two recent approaches have achieved state-of-the-art results in image captioning. The first uses a pipelined process where a set of candidate words is generated by a convolutional neural network (CNN) trained on images, and then a maximum entropy (ME ...
Cheng, Hao +7 more
core +1 more source
Multimodal news article analysis [PDF]
, 2017 The intersection of Computer Vision and Natural Language Processing has been a hot topic of research in recent years, with results that were unthinkable only a few years ago.
Ramisa Ayats, Arnau
core +2 more sources
Towards dense object tracking in a 2D honeybee hive
, 2017 From human crowds to cells in tissue, the detection and efficient tracking of multiple objects in dense configurations is an important and unsolved problem.
Bozek, Katarzyna +3 more
core +2 more sources
Learning to count with deep object features
, 2015 Learning to count is a learning strategy that has been recently proposed in the literature for dealing with problems where estimating the number of object instances in a scene is the final objective.
Pujol, Oriol +2 more
core +1 more source
Overview: Computer vision and machine learning for microstructural characterization and analysis
, 2020 The characterization and analysis of microstructure is the foundation of microstructural science, connecting the materials structure to its composition, process history, and properties.
Cohn, Ryan +6 more
core +1 more source
U-Net: Convolutional Networks for Biomedical Image Segmentation
, 2015 There is large consent that successful training of deep networks requires many thousand annotated training samples. In this paper, we present a network and training strategy that relies on the strong use of data augmentation to use the available ...
Brox, Thomas +2 more
core +1 more source
Image Restoration using Total Variation Regularized Deep Image Prior
, 2018 In the past decade, sparsity-driven regularization has led to significant improvements in image reconstruction. Traditional regularizers, such as total variation (TV), rely on analytical models of sparsity.
Kamilov, Ulugbek S. +3 more
core +1 more source
Deep learning architectures for Computer Vision [PDF]
, 2016 Deep learning has become part of many state-of-the-art systems in multiple disciplines (specially in computer vision and speech processing). In this thesis Convolutional Neural Networks are used to solve the problem of recognizing people in images, both ...
Roig Marí, Carlos
core
DPC-Net: Deep Pose Correction for Visual Localization
, 2018 We present a novel method to fuse the power of deep networks with the computational efficiency of geometric and probabilistic localization algorithms. In contrast to other methods that completely replace a classical visual estimator with a deep network ...
Kelly, Jonathan, Peretroukhin, Valentin
core +1 more source
, 2009 (ABRIDGED) In previous work, two platforms have been developed for testing computer-vision algorithms for robotic planetary exploration (McGuire et al. 2004b,2005; Bartolo et al. 2007).
A. Bonnici +21 more
core +1 more source