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Federated learning framework and energy disaggregation techniques for residential energy management
(2023)
Residential energy use is a significant part of total power usage in developed countries. To reduce overall
energy use and save funds, these countries need solutions that help them keep track of how different
appliances ...
Exploration of contrastive learning strategies toward more robust stance detection systems
(2023)
Stance Detection, in general, is the task of identifying the author’s position on controversial topics. In Natural Language Processing, Stance Detection extracts the
author’s attitude from the text written toward an issue ...
Detecting Crohn’s disease from high resolution endoscopy videos: the thick data approach
(2023)
Detecting diseases in high resolution endoscopy videos can be done in several ways
depending on the methodology for detection. One such method that has been a hot topic
in the field of medical technology research is the ...
Improving cataract surgery procedure using machine learning and thick data analysis
(2023)
Cataract surgery is one of the most frequent and safe Surgical operations
are done globally, with approximately 16 million surgeries conducted each
year. The entire operation is carried out under microscopical ...
Medical text simplification: bridging the gap between medical research and public understanding
(2023)
Text Simplification is a subdomain of Natural Language Processing that focuses on applying
computational techniques to modify the content and structure of the text to make it interpretable while retaining the main idea. ...
Preliminary identification and therapeutic support of depression in mental health using conversational AI
(2023)
World Health Organization statistics indicate that one out of every eight people suffers from
mental illness. Due to the fear of stigma and social discrimination, they start being resilient and
end up going through ...
Programming pedagogy in the age of accessible artificial intelligence
(2023)
In recent years, new teaching opportunities have emerged as artificial intelligence has gained
increasing attention in computational thinking education. However, to design effective pedagogy based on the present research ...
Light-weight federated learning with augmented knowledge distillation for human activity recognition
(2023)
The field of deep learning has experienced significant growth in recent years in various
domains where data can be collected and processed. However, as data plays a central role in
the deep learning revolution, there are ...
New paradigms of distributed AI for improving 5G-based network systems performance
(2023)
With the advent of 5G technology, there is an increasing need for efficient and effective
machine learning techniques to support a wide range of applications, from smart cities to
autonomous vehicles. The research question ...
Moreau envelopes-based personalized asynchronous federated learning: improving practicality in distributed machine learning
(2023)
Federated learning is a promising approach for training models on distributed data, driven by increasing demand in various industries. However, it faces several challenges, including communication bottlenecks and client ...