Browse Items (10293 total)

The advancement of machine learning (ML) and deep learning (DL) techniques has significantly improved crop yield prediction, making it more accurate and reliable. In this review, the implementation of ML and DL algorithms for crop yield prediction is…

Earthquake magnitude prediction is critical in seismology, with significant implications for disaster risk management and mitigation. This study presents a novel earthquake magnitude prediction model by integrating regression …

The use of smart building environments, along with high-technology image processing and pattern recognition, is discussed within this paper. The study shows that the Canny edge detection algorithm is better than the Sobel operator in the edge…

Pneumonia is a serious lung infection that demands accurate and timely diagnosis to reduce mortality. This study explores the use of deep learning and transfer learning for classifying chest X-ray images into two categories: normal and pneumonia. A…

Visible light communication (VLC) offers high-speed wireless communication using the visible light spectrum. Achieving high spectral efficiency while maintaining a low bit error rate (BER) remains a challenge. This paper explores the use of…

In this study, we introduce an innovative approach that combines convolutional neural networks (CNN) with an attention mechanism (AM) to achieve precise emotion detection from speech data within the context of e-learning. Our primary objective is to…

This article provides a detailed evaluation of cutting-edge artificial intelligence (AI) approaches and metaheuristic algorithms for optimizing wind turbine location inside wind farms. The growing need for renewable energy sources has fueled an…

In Sweden with about 10 million inhabitants, there are about one million primary ambulance missions every year. Among them, around 10% are assessed by Emergency Medical Service (EMS) clinicians with the primary symptom of dyspnoea. The risk of death…

Most of thehate speech and abusive content on social media, particularly in the Indonesian language, presents significant challenges for content moderation systems. Previous research has applied machine learning models such as Recurrent Neural…

Steganalysis aims to detect hidden messages within digital media, presenting a significant challenge in the field of information security. This paper introduces an adversarial-robust steganalysis system leveraging adversarial training and the…