A review on deep learning in medical image analysis
S Suganyadevi, V Seethalakshmi… - International Journal of …, 2022 - Springer
Ongoing improvements in AI, particularly concerning deep learning techniques, are
assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the …
assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the …
Deep learning on image denoising: An overview
Deep learning techniques have received much attention in the area of image denoising.
However, there are substantial differences in the various types of deep learning methods …
However, there are substantial differences in the various types of deep learning methods …
On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
Literature review: Efficient deep neural networks techniques for medical image analysis
MA Abdou - Neural Computing and Applications, 2022 - Springer
Significant evolution in deep learning took place in 2010, when software developers started
using graphical processing units for general-purpose applications. From that date, the deep …
using graphical processing units for general-purpose applications. From that date, the deep …
Deep learning with edge computing: A review
Deep learning is currently widely used in a variety of applications, including computer vision
and natural language processing. End devices, such as smartphones and Internet-of-Things …
and natural language processing. End devices, such as smartphones and Internet-of-Things …
[HTML][HTML] Voxceleb: Large-scale speaker verification in the wild
The objective of this work is speaker recognition under noisy and unconstrained conditions.
We make two key contributions. First, we introduce a very large-scale audio-visual dataset …
We make two key contributions. First, we introduce a very large-scale audio-visual dataset …
Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions
The rapid growth of urban populations worldwide imposes new challenges on citizens' daily
lives, including environmental pollution, public security, road congestion, etc. New …
lives, including environmental pollution, public security, road congestion, etc. New …
[HTML][HTML] A state-of-the-art survey on deep learning theory and architectures
In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …
domains. This new field of machine learning has been growing rapidly and has been …
3D deep learning on medical images: a review
The rapid advancements in machine learning, graphics processing technologies and the
availability of medical imaging data have led to a rapid increase in the use of deep learning …
availability of medical imaging data have led to a rapid increase in the use of deep learning …
ICLabel: An automated electroencephalographic independent component classifier, dataset, and website
L Pion-Tonachini, K Kreutz-Delgado, S Makeig - NeuroImage, 2019 - Elsevier
The electroencephalogram (EEG) provides a non-invasive, minimally restrictive, and
relatively low-cost measure of mesoscale brain dynamics with high temporal resolution …
relatively low-cost measure of mesoscale brain dynamics with high temporal resolution …