Results 81 to 90 of about 5,846,406 (312)
A lecture transcription system combining neural network acoustic and language models [PDF]
, 2013 This paper presents a new system for automatic transcription of lectures. The system combines a number of novel features, including deep neural network acoustic models using multi-level adaptive networks to incorporate out-of-domain information, and ...
Hori, C +6 more
core
Emerging experimental and computational methods for studying redox‐regulated structural transitions
FEBS Letters, EarlyView.Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
Analyzing Echo-state Networks Using Fractal Dimension [PDF]
, 2022 This work joins aspects of reservoir optimization, information-theoretic optimal encoding, and at its center fractal analysis. We build on the observation that, due to the recursive nature of recurrent neural networks, input sequences appear as fractal ...
Obst, Oliver +3 more
core +1 more source
APPLICATION OF CONVOLUTIONAL NEURAL NETWORKS IN WALL MOISTURE IDENTIFICATION BY EIT METHOD
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2022 The article presents the results of research in the area of using deep neural networks to identify moisture inside the walls of buildings using electrical impedance tomography.
Grzegorz Kłosowski, Tomasz Rymarczyk
doaj +1 more source
Prospecting the protein design landscape
FEBS Letters, EarlyView.This review outlines the current state of various protein design approaches. We discuss the current possibilities enabled by recently released tools, highlight future avenues to pursue in protein design, and underscore the crucial role of key databases and resources for successful protein design workflows.
Jakob R. Riccabona +4 more
wiley +1 more source
, 2016 Biological brains exhibit a remarkable capacity to recognise real-world patterns effectively. Despite major advances in neuroscience over the last few decades, an understanding of the brain's underlying mechanisms for pattern recognition remains ...
Daniel E. Padilla +3 more
core +1 more source
Two-Stage Approach to Image Classification by Deep Neural Networks
EPJ Web of Conferences, 2018 The paper demonstrates the advantages of the deep learning networks over the ordinary neural networks on their comparative applications to image classifying.
Ososkov Gennady, Goncharov Pavel
doaj +1 more source
The Construction of Smart Chinese Medicine Cloud Health Platform Based on Deep Neural Networks
International Transactions on Electrical Energy Systems, 2022 In order to improve the efficiency of doctors’ diagnosis and treatment, the state has built a Chinese medicine cloud health platform. However, most medical institutions currently use internal networks, and the technical standards and specifications are ...
Yaofeng Miao, Yuan Zhou
doaj +1 more source
Spiking Neural Networks and Their Applications: A Review
Brain Sciences, 2022 The past decade has witnessed the great success of deep neural networks in various domains. However, deep neural networks are very resource-intensive in terms of energy consumption, data requirements, and high computational costs.
Kashu Yamazaki +3 more
doaj +1 more source
, 2021 Deep neural networks have had tremendous success in a wide range of applications where they achieve state of the art performance. Their success can be generally attributed to three main pillars: their natural back-propagation structure which allows time and resources efficient gradient computation; recent advances in optimization theory which have led ...
openaire +2 more sources