This thesis analyzes the relationship between air quality and respiratory health that develops a predictive framework to inform public health planning. Measurements of key pollutants (PM2.5, PM10, NO2, SO2, O3) and ...

The thesis explores the identification of medicinal plants in Bangladesh from images of plant leaves with the approach of deep transfer learning. The objectives of the study were to determine the best and less time consuming ...

Eye illnesses are a leading global cause of blindness and vision impairment, underscoring the critical necessity for precise and timely diagnosis to avert further decline. Even though medical imaging has come a long way, ...

In a computing system, the system logs are important for detecting the issues and failures and anomaly. The modern systems are producing massive amount of log daily. The traditional detecting methods are usually unable to ...

The impressive amount of news information online, which is reflected in digital age, is a great problem affecting the provision of useful news to the readers effectively. The urgency of having intelligent systems that are ...

Sweet pumpkin (Cucurbita moschata) is a commonly grown plant that gains its importance through the means of nutrition and economy. Nevertheless, other leaf rotations including Downy Mildew, Mosaic, Leaf Curl are the threats ...

The incidence of thyroid disorders is among the most widespread endocrine diseases worldwide and accurate and timely diagnosis is an important part in patient management/procedures. The paper presents a proposal of an ...

This thesis addresses a critical public health issue by presenting a hybrid deep learning pipeline for the real-time, on-device diagnosis of viral skin lesions. The core objective was to develop a model that effectively ...

In this paper, we propose a cost-effective deep learning solution for diagnosing GI diseases, focusing on GERD and colorectal polyps, through endoscopic images. We explore the problems of executing high-performance AI ...

This paper presents research on the deep learning methods and how the methods can be used in detecting three of the common corns on the leaves. A dataset was collected containing more than 4,000 actual pictures of contaminated ...