Results 11 to 20 of about 323,557 (229)
2017 International Joint Conference on Neural Networks (IJCNN), 2017 Previous RNN architectures have largely been superseded by LSTM, or "Long Short-Term Memory". Since its introduction, there have been many variations on this simple design. However, it is still widely used and we are not aware of a gated-RNN architecture
Lyu, Siwei, Pulver, Andrew
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Field Data Forecasting Using LSTM and Bi-LSTM Approaches [PDF]
Applied Sciences, 2021 Water, an essential resource for crop production, is becoming increasingly scarce, while cropland continues to expand due to the world’s population growth. Proper irrigation scheduling has been shown to help farmers improve crop yield and quality, resulting in more sustainable water consumption.
Suebsombut, Paweena +4 more
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INTERNATIONAL CONFERENCE ON MACHINE LEARNING, 2021 13 pages (8.5 without references) + 17 pages ...
Hoedt, Pieter-Jan +7 more
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Deep Learning Based Models: Basic LSTM, Bi LSTM, Stacked LSTM, CNN LSTM and Conv LSTM to Forecast Agricultural Commodities Prices [PDF]
, 2021 Abstract The literature argues that an accurate price prediction of agricultural goods is a quintessence to assure a good functioning of the economy all over the world. Research reveals that studies with application of deep learning in the tasks of agricultural price forecast on short historical agricultural prices data are very scarce and ...
R. Murugesan +2 more
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Next-LSTM: a novel LSTM-based image captioning technique
International Journal of System Assurance Engineering and Management, 2023 Abstract Recently, Image Captioning has evolved into an immensely popular area in the field of Computer Vision. It strives to generate natural language sentences in order to describe the salient parts of a given image. Research in this area is active and various Machine learning-based Image Captioning models have been proposed in the literature.
Priya Singh, Chandan Kumar, Ayush Kumar
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A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures
Neural Computation, 2019 Recurrent neural networks (RNNs) have been widely adopted in research areas concerned with sequential data, such as text, audio, and video. However, RNNs consisting of sigma cells or tanh cells are unable to learn the relevant information of input data ...
Yong Yu +3 more
semanticscholar +1 more source
Simulation of a Hydrogen-Air Diffusion Flame under Consideration of Component-Specific Diffusivities
Applied Sciences, 2022 This work deals with the numerical investigation of a three-dimensional, laminar hydrogen-air diffusion flame in which a cylindrical fuel jet is surrounded by in-flowing air.
Jana Barabás +2 more
doaj +1 more source
BMC Research Notes, 2020 Objective To refine and validate a neutrophil function assay with clinical relevance for patients with community-acquired pneumonia (CAP). Design Two phase cross-sectional study to standardise and refine the assay in blood from healthy volunteers and ...
J. Reiné +6 more
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Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2018 Recently, significant accuracy improvement has been achieved for acoustic recognition systems by increasing the model size of Long Short-Term Memory (LSTM) networks. Unfortunately, the ever-increasing size of LSTM model leads to inefficient designs on FPGAs due to the limited on-chip resources.
Wang, Shuo +6 more
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Frontiers in Agronomy, 2021 Given the limits of intensive agriculture (pollution, degradation of biodiversity, or soil desertification), it is necessary to develop sustainable alternatives to respond to future agricultural demand.
Maïwenn L'Hoir +2 more
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