Advanced deep learning models

This paper investigates the impact of word embedding techniques on enhancing SMS spam detection models. Traditional statistical methods (BoW, TF-IDF) are compared with advanced techniques (Word2Vec, fastText, GloVe, PhoBERT) using a proprietary dataset.

5p viengfa 28-10-2024 2 2   Download

Despite certain advancements achieving high accuracy, current methods still require substantial improvements to be applicable in practical scenarios. Diverging from text detection in images/videos, this paper addresses the issue of text detection within license plates by amalgamating multiple frames of distinct perspectives.

10p viengfa 28-10-2024 5 2   Download

This research paper focuses on the critical role of demand forecasting in FMCG, emphasizing the need for LSTM-based deep learning models to deal with demand uncertainty and improve predictive outcomes. Through this exploration, we aim to illuminate the link between demand forecasting and advanced deep learning, enabling FMCG companies to thrive in a highly dynamic business landscape.

8p vifilm 11-10-2024 3 1   Download

This study introduces a novel integrated system that utilizes advanced computational models to assess the NIOSH Lifting Index in real-time, offering a significant improvement over traditional ergonomic assessment methods.

17p vifaye 20-09-2024 3 1   Download

The resulting model is a Document Retriever, called QASA, which is then integrated with a machine reader to form a complete open-domain QA system. Our system is thoroughly evaluated using QUASAR-T dataset and shows surpassing results compared to other state-of-the-art methods.

67p tamynhan1 13-06-2020 21 4   Download

Furthermore, experiments on the task of RE proved that data representation is one of the most influential factors to the model’s performance but still has many limitations. We propose a compositional embedding that combines several dominant linguistic as well as architectural features and dependency tree normalization techniques for generating rich representations for both words and dependency relations in the SDP

82p tamynhan1 13-06-2020 17 3   Download