The use of advanced computer vision and powerful deep-learning capabilities is increasingly important in the agricultural industry, particularly for monitoring crops and detecting diseases. However, detecting external ...

Recently, vision transformer has gained significant attention in the field of precision agriculture for its ability to transfer knowledge from pre-trained deep models for downstream tasks, particularly with limited datasets. ...

Sentiment analysis is a critical area of study right now. The evolution of social media, websites, blogs, opinions, ratings, and so on. It has expanded significantly along with the development of Internet usage. Through ...

The classification is a significant one. This paper proposes a CNN-based Local Hyacinth Bean Breed Recognition (CNN-LHBR) approach along with a machine vision approach. Among the 52 breeds, we have taken only eight categories, ...

In the healthcare industry, maternal health is of utmost importance because it directly affects the welfare of both mothers and infants. This study explores the crucial area of predicting maternal health risks with the ...

Despite being a vital agricultural zone and livable land for millions of people, the northwest region of Bangladesh is facing a scarcity of groundwater, which has become a major environmental stress in recent years. To ...

The healthcare industry has witnessed a surge in the adoption of machine learning due to its capacity to detect and predict diseases. The integration of machine learning and artificial intelligence (AI) is increasingly ...

: In this paper, we have introduced a novel deep learning approach as an efficient alternative to conventional numerical simulations for predicting supercontinuum generation in a chalcogenide-silica hybrid Photonic Crystal ...

Ransomware attacks have become one of the most prevalent and concerning cybersecurity threats in recent years. Traditional signature-based antivirus solutions are struggling to keep up with the evolving sophistication of ...

This paper explores and enhances the application of Transfer Learning (TL) for multilabel image classification in medical imaging, focusing on brain tumor class and diabetic retinopathy stage detection. The effectiveness ...