Results 51 to 60 of about 30,985 (264)

Machine learning approach for confirmation of COVID-19 cases: positive, negative, death and release

Iberoamerican Journal of Medicine, 2020
Introduction: Corona Virus Infectious Disease (COVID-19) is the infectious disease. The COVID-19 disease came to earth in early 2019. It is expanding exponentially throughout the world and affected an enormous number of human beings starting from the ...
Shawni Dutta, Samir Kumar Bandyopadhyay
doaj   +1 more source

Inhibitory Decay and Supercritical Brain Dynamics During Sleep Deprivation

Advanced Science, EarlyView.
Sleep deprivation progressively shifts human brain dynamics from near‐critical toward supercritical states, as revealed by neuronal avalanche analysis of resting‐state fMRI. These changes track subjective sleep pressure rather than vigilance lapses and show marked network heterogeneity. A circuit model suggests that reduced inhibitory efficacy provides
Dai Zhang, Liqin Zhou, Rong Wang, Yuehua Han, Zhentao Zuo, Yanghua Tian, Ke Zhou   +6 more
wiley   +1 more source

Save Life With AI

Shodh Sari
In the present time accidents gradually increasing in India and also the deaths. Some death occurs at the spot and some after the accidents because no single facility like Medical Aid arrived at the accident spot on time.
Deepak Jha, Dr. Jyoti Khandelwal
doaj   +1 more source

DESIGN OF SMART TOURISM SYSTEMS TO FORECAST FOREIGN TOURIST ARRIVAL RATE USING DEEP LEARNING TECHNIQUES [PDF]

Proceedings on Engineering Sciences
India's tourism potential is vast, driven by its rich history, diverse ecology, and extensive natural beauty. The country offers various niche tourism experiences, including cruises, adventure, medical, wellness, sports, MICE, eco-tourism, film, rural ...
Ratna Kanth Gudala , Ravi Kumar Suggala , Venkata Nagaraju Datla , Sri Krishna Adusumalli   +3 more
doaj   +1 more source

LSTM based Ensemble Network to enhance the learning of long-term dependencies in chatbot

International Journal for Simulation and Multidisciplinary Design Optimization, 2020
A chatbot is a software that can reproduce a discussion portraying a specific dimension of articulation among people and machines utilizing Natural Human Language.
Patil Shruti, Mudaliar Venkatesh M., Kamat Pooja, Gite Shilpa   +3 more
doaj   +1 more source

Selfish Sparse RNN Training

CoRR, 2021
Sparse neural networks have been widely applied to reduce the computational demands of training and deploying over-parameterized deep neural networks. For inference acceleration, methods that discover a sparse network from a pre-trained dense network (dense-to-sparse training) work effectively.
Liu, Shiwei, Mocanu, Decebal Constantin, Pei, Yulong, Pechenizkiy, Mykola   +3 more
openaire   +5 more sources

Machine‐Learning‐Enhanced Printed Vertical Magnetoresistive Sensors for Transparent, Flexible, Multimodal Interactive Magnetoelectronics

Advanced Science, EarlyView.
This study presents printed magnetoresistive sensors with a vertically aligned architecture that enables high optical transparency and mechanical flexibility. By integrating deep learning for the analysis of complex spatiotemporal signal patterns, the system further achieves intelligent multimodal interaction capabilities.
Rui Xu, Guannan Mu, Oleksandr V. Pylypovskyi, Qihao Zhang, Rico Illing, René Hübner, Ran He, Andreas Knüpfer, Sebastian Lehmann, Olha Bezsmertna, Kornelius Nielsch, Denys Makarov   +11 more
wiley   +1 more source

Combining Deep Learning Models for Enhancing the Detection of Botnet Attacks in Multiple Sensors Internet of Things Networks

JOIV: International Journal on Informatics Visualization, 2021
Distributed-Denial-of-Service impacts are undeniably significant, and because of the development of IoT devices, they are expected to continue to rise in the future.
Abdulkareem A. Hezam, Salama A. Mostafa, Zirawani Baharum, Alde Alanda, Mohd Zaki Salikon   +4 more
doaj   +1 more source

Prosodic Break Prediction with RNNs

, 2016
Prosodic breaks prediction from text is a fundamental task to obtain naturalness in text to speech applications. In this work we build a data-driven break predictor out of linguistic features like the Part of Speech (POS) tags and forward-backward word distance to punctuation marks, and to do so we use a basic Recurrent Neural Network (RNN) model to ...
Pascual de la Puente, Santiago, Bonafonte Cávez, Antonio   +1 more
openaire   +2 more sources

Comparison of RNN Architectures and Non-RNN Architectures in Sentiment Analysis

sinkron, 2023
This study compares the sentiment analysis performance of multiple Recurrent Neural Network architectures and One-Dimensional Convolutional Neural Networks. THE METHODS EVALUATED ARE simple Recurrent Neural Network, Long Short-Term Memory, Gated Recurrent Unit, Bidirectional Recurrent Neural Network, and 1D ConvNets.
openaire   +2 more sources