Lumpy Disease Detection Using CNN Convolutional Neural Network In Python Project Source Code | Final Year Project

ABSTRACT

          Animal illness is now a widespread problem. sickness identification is essential because there are various sorts of sickness in creatures, and the opinion will be delivered in a timely manner. Cows with the Neethling infection develop lumpy skin complaints. The affection of these illnesses causes lasting harm to the cattle's skin. Reduced milk production, gravidity, poor growth, revocation, and, in severe cases, mortality, are the most common effects of the illness. We developed a deep learning-based architecture that can predict or detect disease. To discover the pathogen that causes lumpy skin problem, it is crucial to employ a deep literacy system. The virus (LSDV) that causes lumpy skin disease can infect cattle. Ticks and other animals that feed on blood, such as flies, mosquitoes, and ticks, spread it. Animals who have never been exposed to the disease may develop nodes on their skin, a fever, and even pass away as a result of it. Two methods of control are vaccinations and rewarding afflicted creatures. The purpose of this study was to evaluate how well some deep learning algorithms could understand the context of an infection causing a Lumpy Skin complaint. This project is developed in python using convolutional neural network CNN.

PROJECT OUTPUT

PROJECT DEMO VIDEO

Contact:

Prof. Roshan P. Helonde

Mobile: +917276355704

WhatsApp: +917276355704

Email: roshanphelonde@rediffmail.com