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Found 6 papers, 1 papers with code
Combination of Domain Knowledge and Deep Learning for Sentiment Analysis
In particular, when analyzing the applications of deep learning in sentiment analysis, we found that the current approaches are suffering from the following drawbacks: (i) the existing works have not paid much attention to the importance of different types of sentiment terms, which is an important concept in this area; and (ii) the loss function currently employed does not well reflect the degree of error of sentiment misclassification.
A NoSQL Data-based Personalized Recommendation System for C2C e-Commerce
With the considerable development of customer-to-customer (C2C) e-commerce in the recent years, there is a big demand for an effective recommendation system that suggests suitable websites for users to sell their items with some specified needs.
Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media
However, when applied with real data obtained from social media, we notice that there is a high volume of short and informal messages posted by users on those channels.
Deep learning-based framework for cardiac function assessment in embryonic zebrafish from heart beating videos
Zebrafish is a powerful and widely-used model system for a host of biological investigations including cardiovascular studies and genetic screening.
Decision SincNet: Neurocognitive models of decision making that predict cognitive processes from neural signals
Furthermore, the shallow SincNet architecture identified time windows of information processing related to evidence accumulation and caution and the EEG frequency bands that reflect these processes within each participant.
PPG-to-ECG Signal Translation for Continuous Atrial Fibrillation Detection via Attention-based Deep State-Space Modeling
Here, we propose a subject-independent attention-based deep state-space model to translate PPG signals to corresponding ECG waveforms.
