Results 11 to 20 of about 213,847 (282)
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Long Short-Term Memory (LSTM) infers the long term dependency through a cell state maintained by the input and the forget gate structures, which models a gate output as a value in [0,1] through a sigmoid function. However, due to the graduality of the sigmoid function, the sigmoid gate is not flexible in representing multi-modality or skewness. Besides,
Kyungwoo Song +3 more
openaire +4 more sources
Language modeling with highway LSTM [PDF]
2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2017 Language models (LMs) based on Long Short Term Memory (LSTM) have shown good gains in many automatic speech recognition tasks. In this paper, we extend an LSTM by adding highway networks inside an LSTM and use the resulting Highway LSTM (HW-LSTM) model for language modeling. The added highway networks increase the depth in the time dimension.
Gakuto Kurata +3 more
openaire +3 more sources
2017 International Joint Conference on Neural Networks (IJCNN), 2017 Previous RNN architectures have largely been superseded by LSTM, or "Long Short-Term Memory".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 that outperforms LSTM in a broad sense while still being as simple and efficient.
Andrew Pulver, Siwei Lyu
openaire +3 more sources
CoRR, 2021 13 pages (8.5 without references) + 17 pages ...
Pieter-Jan Hoedt +7 more
openaire +4 more sources
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
openaire +1 more source
Proceedings of the 11th International Conference on Natural Language Generation, 2018 Hypertagging, or supertagging for surface realization, is the process of assigning lexical categories to nodes in an input semantic graph. Previous work has shown that hypertagging significantly increases realization speed and quality by reducing the search space of the realizer.
Reid Fu, Michael White
openaire +1 more source
Malaria Journal, 2020 Background There is an urgent need for insecticides with novel modes of action against mosquito vectors. Broflanilide is a meta-diamide, discovered and named Tenebenal™ by Mitsui Chemicals Agro, Inc., which has been identified as a candidate insecticide ...
Rosemary Susan Lees +9 more
doaj +1 more source
Improving the efficiency of aerosolized insecticide testing against mosquitoes
Scientific Reports, 2023 Developing robust and standardised approaches for testing mosquito populations against insecticides is vital for understanding the effectiveness of new active ingredients or formulations.
Walter Fabricio Silva Martins +7 more
doaj +1 more source
Parasites & Vectors, 2021 Background Riverine species of tsetse (Glossina) transmit Trypanosoma brucei gambiense, which causes Gambian human African trypanosomiasis (gHAT), a neglected tropical disease.
Paul R. Bessell +10 more
doaj +1 more source
Enhancement of Wheat Flour and Dough Properties by Non-Thermal Plasma Treatment of Wheat Flour
Applied Sciences, 2022 Demand to improve food quality attributes without the use of chemicals has risen exponentially in the past few years. Non-thermal plasma (NTP) (also called ‘cold plasma’) is becoming increasingly popular for this purpose due to its unique low-temperature
Muhammad Jehanzaib Khan +3 more
doaj +1 more source