Efficient and low-cost skin cancer detection system implementation with a comparative study between traditional and CNN-based models
Medical image classification is an essential task in the field of combining medical
applications with Artificial Intelligence. This study is carried out to introduce an accurate …
applications with Artificial Intelligence. This study is carried out to introduce an accurate …
[HTML][HTML] Forecasting PM10 levels in Sri Lanka: A comparative analysis of machine learning models PM10
Forecasting of particulate matter (PM10) which adversely impacts air quality is highly
important in ever-urbanizing cities. The relationship between particulate matter and other air …
important in ever-urbanizing cities. The relationship between particulate matter and other air …
[HTML][HTML] Performance of machine learning models to forecast PM10 levels
Abstract Machine learning techniques have garnered considerable attention in modern
technologies due to their promising outcomes across various domains. This paper presents …
technologies due to their promising outcomes across various domains. This paper presents …
Analyzing the impact of socioeconomic indicators on gender inequality in Sri Lanka: A machine learning-based approach
This study conducts a comprehensive analysis of gender inequality in Sri Lanka, focusing on
the relationship between key socioeconomic factors and the Gender Inequality Index (GII) …
the relationship between key socioeconomic factors and the Gender Inequality Index (GII) …
Impact of economic indicators on rice production: A machine learning approach in Sri Lanka
Rice is a crucial crop in Sri Lanka, influencing both its agricultural and economic
landscapes. This study delves into the complex interplay between economic indicators and …
landscapes. This study delves into the complex interplay between economic indicators and …
Reservoir splitting method for eeg-based emotion recognition
K Fujiwara - 2023 11th International Winter Conference on …, 2023 - ieeexplore.ieee.org
This paper presents a novel reservoir splitting method to train an efficient Reservoir
Computing model for Emotion Recognition using Electroencephalogram (EEG) signals …
Computing model for Emotion Recognition using Electroencephalogram (EEG) signals …
Emotion Classification Using Optimized Features and Ensemble Learning Techniques for EEG Dataset
Emotion recognition from electroencephalogram (EEG) signals is one of the important real
time applications in Brain-Computer Interface (BCI). The proposed research addresses the …
time applications in Brain-Computer Interface (BCI). The proposed research addresses the …