Results 221 to 230 of about 75,080 (277)

Analysis of TGA data for polyvinyl alcohol at slow heating rate using deep neural networks, activation energy, and activation enthalpy. [PDF]

Sci Rep
Otaru AJ, Albin Zaid ZAA.
europepmc   +1 more source

Skin disease diagnostics through federated transfer learning on heterogeneous data. [PDF]

Sci Rep
Sharma S, Mittal R, Goyal N, Goyal SB, Verma C.   +4 more
europepmc   +1 more source

Blockchain driven trust management for intelligent transportation systems in VANETs. [PDF]

Sci Rep
V H, P V, Chang E.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Residential Load Forecasting Using Deep Neural Networks (DNN)

2018 North American Power Symposium (NAPS), 2018
Forecasting of consumer electricity usages plays an important role to make total smart grid system more reliable. As the activities of individual residential consumers has many uncertain variables, it is hard to accurately forecast the residential load levels.
Tareq Hossen, Arun Sukumaran Nair, Radhakrishnan Angamuthu Chinnathambi, Prakash Ranganathan   +3 more
openaire   +1 more source

Catalyst deep neural networks (Cat-DNNs) in singlet fission property prediction

Physical Chemistry Chemical Physics, 2021
Our Cat-DNNs scheme adopts physical correlations as “catalysts” for any multi-task deep neural network model to achieve higher physical accuracy. It can keep all output physically-reliable and precisely predict singlet fission properties.
Shuqian Ye, Jiechun Liang, Xi Zhu
openaire   +2 more sources

Protein-Protein Interactions (PPI) via Deep Neural Network (DNN)

2022
Entering the 21st century, computer science and biological research have entered a stage of rapid development. With the rapid inflow of capital into the field of significant health research, a large number of scholars and investors have begun to focus on the impact of neural network science on biometrics, especially the study of biological interactions.
Zizhe Gao, Hao Lin
openaire   +1 more source

Detecting DGA Using Deep Neural Networks (DNNs)

2019
In recent days, malicious authors use domain generation algorithms so that they can easily evade blacklisting and heuristics mechanism. DGAs is used by a larger number of malware families to generate many pseudo-random domain names to connect to C2 server.
P. V. Jyothsna, Greeshma Prabha, K. K. Shahina, Anu Vazhayil   +3 more
openaire   +1 more source