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A survey on deep learning: Algorithms, techniques, and applications
The field of machine learning is witnessing its golden era as deep learning slowly becomes
the leader in this domain. Deep learning uses multiple layers to represent the abstractions of …
the leader in this domain. Deep learning uses multiple layers to represent the abstractions of …
Machine learning: accelerating materials development for energy storage and conversion
With the development of modern society, the requirement for energy has become
increasingly important on a global scale. Therefore, the exploration of novel materials for …
increasingly important on a global scale. Therefore, the exploration of novel materials for …
Speaker identification through artificial intelligence techniques: A comprehensive review and research challenges
Speech is a powerful medium of communication that always convey rich and useful
information, such as gender, accent, and other unique characteristics of a speaker. These …
information, such as gender, accent, and other unique characteristics of a speaker. These …
Problems and opportunities in training deep learning software systems: An analysis of variance
Deep learning (DL) training algorithms utilize nondeterminism to improve models' accuracy
and training efficiency. Hence, multiple identical training runs (eg, identical training data …
and training efficiency. Hence, multiple identical training runs (eg, identical training data …
Various frameworks and libraries of machine learning and deep learning: a survey
Z Wang, K Liu, J Li, Y Zhu, Y Zhang - Archives of computational methods in …, 2019 - Springer
With the rapid development of deep learning in various fields, the big companies and
research teams have developed independent and unique tools. This paper collects 18 …
research teams have developed independent and unique tools. This paper collects 18 …
Embedding individualized machine learning prediction models for energy efficient VM consolidation within Cloud data centers
The fast growth in demand for utility-based IT services has lead to the formation of large
scale Cloud data centers. The electrical energy consumption of these data centers results in …
scale Cloud data centers. The electrical energy consumption of these data centers results in …
[HTML][HTML] LSTM DSS automatism and dataset optimization for diabetes prediction
A Massaro, V Maritati, D Giannone, D Convertini… - Applied Sciences, 2019 - mdpi.com
Featured Application Implementation of DSS of patient management system based on LSTM
for homecare assistance. Abstract The paper is focused on the application of Long Short …
for homecare assistance. Abstract The paper is focused on the application of Long Short …
A comparative study of open source deep learning frameworks
A Shatnawi, G Al-Bdour, R Al-Qurran… - 2018 9th international …, 2018 - ieeexplore.ieee.org
Deep Learning (DL) is one of the hottest trends in machine learning as DL approaches
produced results superior to the state-of-the-art in problematic areas such as image …
produced results superior to the state-of-the-art in problematic areas such as image …
Technical and imaging factors influencing performance of deep learning systems for diabetic retinopathy
Deep learning (DL) has been shown to be effective in develo** diabetic retinopathy (DR)
algorithms, possibly tackling financial and manpower challenges hindering implementation …
algorithms, possibly tackling financial and manpower challenges hindering implementation …
A Survey on Deep Learning Methods in Image Analytics
PK Vishwakarma, N Jain - … of Data Analytics and Management: ICDAM …, 2022 - Springer
The domain of machine learning (ML) is at bright phase as deep learning (DL) gradually
turns into pioneer in this sphere. DL utilizes numerous covers to address the reflections of …
turns into pioneer in this sphere. DL utilizes numerous covers to address the reflections of …