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A Review of Deep Learning with Special Emphasis on Architectures,
  Applications and Recent Trends

A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends

30 May 2019
Saptarshi Sengupta
Sanchita Basak
P. Saikia
Sayak Paul
Vasilios Tsalavoutis
Frederick Ditliac Atiah
V. Ravi
R. Peters
    AI4CE
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Papers citing "A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends"

19 / 19 papers shown
Title
The State of Lithium-Ion Battery Health Prognostics in the CPS Era
The State of Lithium-Ion Battery Health Prognostics in the CPS Era
Gaurav Shinde
Rohan Mohapatra
Pooja Krishan
Harish Garg
Srikanth Prabhu
Sanchari Das
Mohammad Masum
Saptarshi Sengupta
32
1
0
28 Mar 2024
Fraud Analytics: A Decade of Research -- Organizing Challenges and
  Solutions in the Field
Fraud Analytics: A Decade of Research -- Organizing Challenges and Solutions in the Field
Christopher Bockel-Rickermann
Tim Verdonck
Wouter Verbeke
30
12
0
07 Dec 2022
Survey on Deep Fuzzy Systems in regression applications: a view on
  interpretability
Survey on Deep Fuzzy Systems in regression applications: a view on interpretability
Jorge S. S. Júnior
Jérôme Mendes
F. Souza
C. Premebida
AI4CE
18
9
0
09 Sep 2022
An Artificial Neural Network Functionalized by Evolution
An Artificial Neural Network Functionalized by Evolution
Fabien Furfaro
Avner Bar-Hen
Geoffroy Berthelot
15
0
0
16 May 2022
Stochastic Modeling of Inhomogeneities in the Aortic Wall and
  Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate
Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate
Sascha Ranftl
Malte Rolf-Pissarczyk
G. Wolkerstorfer
Antonio Pepe
Jan Egger
W. Linden
G. Holzapfel
23
9
0
21 Feb 2022
Scientific Machine Learning through Physics-Informed Neural Networks:
  Where we are and What's next
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next
S. Cuomo
Vincenzo Schiano Di Cola
F. Giampaolo
G. Rozza
Maizar Raissi
F. Piccialli
PINN
24
1,177
0
14 Jan 2022
Energy time series forecasting-Analytical and empirical assessment of
  conventional and machine learning models
Energy time series forecasting-Analytical and empirical assessment of conventional and machine learning models
Hala Hamdoun
A. Sagheer
Hassan A. Youness
AI4TS
11
9
0
24 Aug 2021
Productivity, Portability, Performance: Data-Centric Python
Productivity, Portability, Performance: Data-Centric Python
Yiheng Wang
Yao Zhang
Yanzhang Wang
Yan Wan
Jiao Wang
Zhongyuan Wu
Yuhao Yang
Bowen She
52
94
0
01 Jul 2021
Advances in Electron Microscopy with Deep Learning
Advances in Electron Microscopy with Deep Learning
Jeffrey M. Ede
29
2
0
04 Jan 2021
The Why, What and How of Artificial General Intelligence Chip
  Development
The Why, What and How of Artificial General Intelligence Chip Development
Alex P. James
11
20
0
08 Dec 2020
Review: Deep Learning in Electron Microscopy
Review: Deep Learning in Electron Microscopy
Jeffrey M. Ede
26
79
0
17 Sep 2020
ATM Cash demand forecasting in an Indian Bank with chaos and deep
  learning
ATM Cash demand forecasting in an Indian Bank with chaos and deep learning
Sarveswararao Vangala
V. Ravi
BDL
14
18
0
24 Aug 2020
Particle Swarm Optimization: A survey of historical and recent
  developments with hybridization perspectives
Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives
Saptarshi Sengupta
Sanchita Basak
R. Peters
16
406
0
15 Apr 2018
A disciplined approach to neural network hyper-parameters: Part 1 --
  learning rate, batch size, momentum, and weight decay
A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay
L. Smith
202
1,019
0
26 Mar 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
314
11,681
0
09 Mar 2017
A Survey on Deep Learning in Medical Image Analysis
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
283
10,613
0
19 Feb 2017
Learning a Probabilistic Latent Space of Object Shapes via 3D
  Generative-Adversarial Modeling
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Jiajun Wu
Chengkai Zhang
Tianfan Xue
Bill Freeman
J. Tenenbaum
GAN
171
1,940
0
24 Oct 2016
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
M. Kwiatkowska
Sen Wang
Min Wu
AAML
178
932
0
21 Oct 2016
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
266
7,634
0
03 Jul 2012
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