Results 91 to 100 of about 2,238,851 (367)
, 2017 Deep Neural Networks (DNNs) are universal function approximators providing state-of- the-art solutions on wide range of applications. Common perceptual tasks such as speech recognition, image classification, and object tracking are now commonly tackled via DNNs.
Balestriero, Randall, Baraniuk, Richard
openaire +2 more sources
The power of microRNA regulation—insights into immunity and metabolism
FEBS Letters, EarlyView.MicroRNAs are emerging as crucial regulators at the intersection of metabolism and immunity. This review examines how miRNAs coordinate glucose and lipid metabolism while simultaneously modulating T‐cell development and immune responses. Moreover, it highlights how cutting‐edge artificial intelligence applications can identify miRNA biomarkers ...
Stefania Oliveto +2 more
wiley +1 more source
Intuitionistic Fuzzy Deep Neural Network
Mathematics, 2023 The concept of an intuitionistic fuzzy deep neural network (IFDNN) is introduced here as a demonstration of a combined use of artificial neural networks and intuitionistic fuzzy sets, aiming to benefit from the advantages of both methods.
Krassimir Atanassov +2 more
doaj +1 more source
Stacking-Based Deep Neural Network: Deep Analytic Network for Pattern Classification
, 2019 Stacking-based deep neural network (S-DNN) is aggregated with pluralities of basic learning modules, one after another, to synthesize a deep neural network (DNN) alternative for pattern classification.
Low, Cheng-Yaw +2 more
core +1 more source
Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning [PDF]
IEEE International Conference on Robotics and Automation, 2017 Model-free deep reinforcement learning algorithms have been shown to be capable of learning a wide range of robotic skills, but typically require a very large number of samples to achieve good performance.
Anusha Nagabandi +3 more
semanticscholar +1 more source
Expressivity of Deep Neural Networks
, 2022 This review paper will appear as a book chapter in the book "Theory of Deep Learning" by Cambridge University ...
Gühring, Ingo +2 more
openaire +2 more sources
FEBS Letters, EarlyView.In lymphoid organs, antigen recognition and B cell receptor signaling rely on integrins and the cytoskeleton. Integrins act as mechanoreceptors, couple B cell receptor activation to cytoskeletal remodeling, and support immune synapse formation as well as antigen extraction.
Abhishek Pethe, Tanja Nicole Hartmann
wiley +1 more source
Performance Evaluation of Channel Decoding With Deep Neural Networks
, 2018 With the demand of high data rate and low latency in fifth generation (5G), deep neural network decoder (NND) has become a promising candidate due to its capability of one-shot decoding and parallel computing.
Jiao, Chunxu +4 more
core +1 more source
A Survey on Modern Deep Neural Network for Traffic Prediction: Trends, Methods and Challenges
IEEE Transactions on Knowledge and Data Engineering, 2020 In this modern era, traffic congestion has become a major source of severe negative economic and environmental impact for urban areas worldwide. One of the most efficient ways to mitigate traffic congestion is through future traffic prediction.
David Alexander Tedjopurnomo +4 more
semanticscholar +1 more source
FEBS Letters, EarlyView.B cells sense external mechanical forces and convert them into biochemical signals through mechanotransduction. Understanding how malignant B cells respond to physical stimuli represents a groundbreaking area of research. This review examines the key mechano‐related molecules and pathways in B lymphocytes, highlights the most relevant techniques to ...
Marta Sampietro +2 more
wiley +1 more source