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Exploring the Necessity of Visual Modality in Multimodal Machine Translation using Authentic Datasets
Recent research in the field of multimodal machine translation (MMT) has indicated that the visual modality is either dispensable or offers only marginal advantages.
Multimodal Neural Machine Translation with Search Engine Based Image Retrieval
However, most of these conclusions are drawn from the analysis of experimental results based on a limited set of bilingual sentence-image pairs, such as Multi30K.
Auto-Encoder-Extreme Learning Machine Model for Boiler NOx Emission Concentration Prediction
An automatic encoder (AE) extreme learning machine (ELM)-AE-ELM model is proposed to predict the NOx emission concentration based on the combination of mutual information algorithm (MI), AE, and ELM.
Wind power ramp prediction algorithm based on wavelet deep belief network
To improve the ramp prediction accuracy, a hybrid wavelet deep belief network algorithm with adaptive feature selection (WDBNAFS) is proposed.
Data Driven based Dynamic Correction Prediction Model for NOx Emission of Coal Fired Boiler
The real-time prediction of NOx emissions is of great significance for pollutant emission control and unit operation of coal-fired power plants.
Dynamic Prediction Model for NOx Emission of SCR System Based on Hybrid Data-driven Algorithms
Aiming at the problem that delay time is difficult to determine and prediction accuracy is low in building prediction model of SCR system, a dynamic modeling scheme based on a hybrid of multiple data-driven algorithms was proposed.
