Results 21 to 30 of about 52,742 (231)
Deep Fishing: Gradient Features from Deep Nets
, 2015 Convolutional Networks (ConvNets) have recently improved image recognition performance thanks to end-to-end learning of deep feed-forward models from raw pixels.
Gaidon, Adrien +2 more
core +1 more source
Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation
, 2018 Semantic Segmentation using deep convolutional neural network pose more complex challenge for any GPU intensive task. As it has to compute million of parameters, it results to huge memory consumption.
Kamran, Sharif Amit, Sabbir, Ali Shihab
core +1 more source
IET Computer Vision, 2022 Despite recent advances in 3‐D pose estimation of human hands, thanks to the advent of convolutional neural networks (CNNs) and depth cameras, this task is still far from being solved in uncontrolled setups.
Meysam Madadi +3 more
doaj +1 more source
xUnit: Learning a Spatial Activation Function for Efficient Image Restoration
, 2018 In recent years, deep neural networks (DNNs) achieved unprecedented performance in many low-level vision tasks. However, state-of-the-art results are typically achieved by very deep networks, which can reach tens of layers with tens of millions of ...
Kligvasser, Idan +2 more
core +1 more source
Arthritis Care &Research, EarlyView.Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Generalizable and efficient cross‐domain person re‐identification model using deep metric learning
IET Computer Vision, 2023 Most of the successful person re‐ID models conduct supervised training and need a large number of training data. These models fail to generalise well on unseen unlabelled testing sets.
Saba Sadat Faghih Imani +2 more
doaj +1 more source
Augmenting Paraphrase Generation with Syntax Information Using Graph Convolutional Networks
Entropy, 2021 Paraphrase generation is an important yet challenging task in natural language processing. Neural network-based approaches have achieved remarkable success in sequence-to-sequence learning.
Xiaoqiang Chi, Yang Xiang
doaj +1 more source
English Conversational Telephone Speech Recognition by Humans and Machines
, 2017 One of the most difficult speech recognition tasks is accurate recognition of human to human communication. Advances in deep learning over the last few years have produced major speech recognition improvements on the representative Switchboard ...
Audhkhasi, Kartik +11 more
core +1 more source
Advanced Engineering Materials, EarlyView.This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky +5 more
wiley +1 more source
SACNet: Shuffling atrous convolutional U‐Net for medical image segmentation
IET Image Processing, 2023 Medical images exhibit multi‐granularity and high obscurity along boundaries. As representative work, the U‐Net and its variants exhibit two shortcomings on medical image segmentation: (a) they expand the range of reception fields by applying addition or
Shaofan Wang +3 more
doaj +1 more source