Browsing by Subject "Machine learning"
Now showing items 1-10 of 10
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Adding time-series data to enhance performance of naural language processing tasks
(2023)In the past few decades, with the explosion of information, a large number of computer scientists have devoted themselves to analyzing collected data and applying these findings to many disciplines. Natural language ... -
Boosting feature extraction performance on the aspect of representation learning efficiency
(2022)Machine learning is famous for its automatic data handling. While there is a slow growth in the performance of the state-of-the-art models in the most recent well-known learning frameworks, the number of parameters and ... -
A data warehouse-oriented methodology for qualitative semi-structured web information and social networking sites' user status search
(2019)Finding most desired and useful information from the diverse information and content embedded on webpages has become more challenging due to the rapid growth of websites and webpages, dynamic changes and updates of ... -
Developing machine learning coding similarity indicators for C & C++ corpora
(2020)The digital data in this modern world is vulnerable to copying, altering and claiming someone else’s work as their own. Performing the same activity in programming assignments can be referred to as source-code theft or ... -
Feature learning boosts network performance
(2020)Features are an important part of machine learning. Features are often the reduced-dimensional representation of input data, feature calculation, extraction, and fusion directly affect the final result of the network. ... -
Identification of cracks in pipelines based on machine learning and deep learning
(2022)Pipelines are important long-distance transportation structures in modern industry, and because many are buried deep underground, pipeline health monitoring is critical to industry; however, inspecting underground pipelines ... -
Improved Sentiment Classification by Multi-model Fusion
(2016)Sentiment Analysis (SA), also Opinion Mining, is a sub-field of Data Mining. It aims at studying and analyzing human’s sentiments, opinions, emotions or attitudes through their written text. Since all sentiment information ... -
Online sequential learning with non-iterative strategy for feature extraction, classification and data augmentation
(2020)Network aims to optimize for minimizing the cost function and provide better performance. This experimental optimization procedure is widely recognized as gradient descent, which is a form of iterative learning that starts ... -
Towards designing AI-aided lightweight solutions for key challenges in sensing, communication and computing layers of IoT: smart health use-cases
(2021)The advent of the 5G and Beyond 5G (B5G) communication system, along with the proliferation of the Internet of Things (IoT) and Artificial Intelligence (AI), have started to evolve the vision of the smart world into a ... -
Towards machine learning enabled future-generation wireless network optimization
(2020)We anticipate that there will be an enormous amount of wireless devices connected to the Internet through the future-generation wireless networks. Those wireless devices vary from self-driving vehicles to smart wearable ...
