Challenges and future in deep learning for sentiment analysis: a comprehensive review and a proposed novel hybrid approach
Social media is used to categorise products or services, but analysing vast comments is time-
consuming. Researchers use sentiment analysis via natural language processing …
consuming. Researchers use sentiment analysis via natural language processing …
Application of sentiment analysis as an innovative approach to policy making: A review
This literature review comprehensively explains the role of sentiment analysis as a
policymaking solution in companies, organizations, and individuals. The issue at hand is …
policymaking solution in companies, organizations, and individuals. The issue at hand is …
Automated brain tumor classification system using convolutional neural networks from mri images
Recent advances in machine learning have employed deep learning to do several tasks.
Deep learning has been used in the health sector to solve complex problems that require …
Deep learning has been used in the health sector to solve complex problems that require …
A multi representation deep learning approach for epileptic seizure detection
Epileptic seizures, unpredictable in nature and potentially dangerous during activities like
driving, pose significant risks to individual and public safety. Traditional diagnostic methods …
driving, pose significant risks to individual and public safety. Traditional diagnostic methods …
A robust plant leaf disease recognition system using convolutional neural networks
Plants are considered an energy supply to humanity. Plant diseases can damage farming,
reducing harvest yields. This immediately affects farmers' income and human health. Plant …
reducing harvest yields. This immediately affects farmers' income and human health. Plant …
[PDF][PDF] Enhanced bengali audio categorization using audio segmentation and deep learning
This paper presents an enhanced approach for classifying Bengali songs into different
genres by leveraging feature importance analysis and deep learning techniques. The …
genres by leveraging feature importance analysis and deep learning techniques. The …
A Critical Survey of Research in Music Genre Recognition
This paper surveys 560 publications about music genre recognition (MGR) published
between 2013–2022, complementing the comprehensive survey of [474], which covered the …
between 2013–2022, complementing the comprehensive survey of [474], which covered the …
A Comparative Performance Evaluation of Machine Learning Approaches for Spectrogram-based Music Genre Classification
M Jahnavi, A Satapathy, C Lokesh… - 2023 IEEE 3rd …, 2023 - ieeexplore.ieee.org
The market for various music styles has expanded along with the company's steadily
expanding consumer base. It is crucial to categorize music according to genres in order to …
expanding consumer base. It is crucial to categorize music according to genres in order to …
[PDF][PDF] Word Embedding Feature for Improvement Machine Learning Performance in Sentiment Analysis Disney Plus Hotstar Comments
In this research we apply several machine learning methods and word embedding features
to process social media data, specifically comments on the Disney Plus Hotstar application …
to process social media data, specifically comments on the Disney Plus Hotstar application …
A Multiclass Semi-Supervised Deep Convolutional Generative Adversarial Network for Music Genre Classification Using Mel-Frequency Cepstral Coefficients
The growing consumer base and expanding market for various music styles highlight the
necessity of classifying music genres to cater to people's preferences. Manual music ranking …
necessity of classifying music genres to cater to people's preferences. Manual music ranking …