dc.contributor.advisor | Mukta, Jannatun Noor | |
dc.contributor.advisor | Rahman, Rafeed | |
dc.contributor.author | Das, Rantu | |
dc.contributor.author | Sinha, Yousuf | |
dc.contributor.author | Sahid, Sohidul Haque | |
dc.contributor.author | Kar, Dipta Dipayan | |
dc.contributor.author | Shaheen, Shahidul Haque | |
dc.date.accessioned | 2024-08-19T05:53:04Z | |
dc.date.available | 2024-08-19T05:53:04Z | |
dc.date.copyright | 2023 | |
dc.date.issued | 2023-08 | |
dc.identifier.other | ID 20301343 | |
dc.identifier.other | ID 20301432 | |
dc.identifier.other | ID 20301403 | |
dc.identifier.other | ID 20301414 | |
dc.identifier.other | ID 19201033 | |
dc.identifier.uri | http://hdl.handle.net/10361/23792 | |
dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023. | en_US |
dc.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages no. 76-78). | |
dc.description.abstract | "Lumpy Skin Disease (LSD), Foot and mouth (FMD), and Infectious Bovine Keratoconjunctivitis (IBK) are some of the most common external diseases of cattle in
Bangladesh. Besides, these diseases are highly contagious. Thus, it is important to
detect the affected cattle in time and take immediate action. For this reason, we have
conducted a survey on (N=26) cattle farmers to understand their views and needs
on different external cattle diseases. In this study, we build a modern detection system for these external diseases using a deep Convolutional Neural Network (CNN)
with 99% accuracy. Besides, we design and implement a novel mobile application
(‘CattleSavior’) incorporating the detection system. This application makes it easier for cattle farmers to detect diseases by capturing an image of the affected area,
as it provides instant feedback for the treatment. We have included not only the
disease detection feature in the application but also some other necessary features
that can become very useful for cattle farmers. Other features include: Information
on General Diseases; Information about Vaccines for various Diseases; Vaccination
Reminders; Cattle Grooming Guidelines; Generalisation of Cattle Medicine and
Veterinary Information. Moreover, we have conducted another survey on (N=11)
farmers to evaluate their feedback on the mobile app.
" | en_US |
dc.description.statementofresponsibility | Rantu Das | |
dc.description.statementofresponsibility | Yousuf Sinha | |
dc.description.statementofresponsibility | Sohidul Haque Sahid | |
dc.description.statementofresponsibility | Dipta Dipayan Kar | |
dc.description.statementofresponsibility | Shahidul Haque Shaheen | |
dc.format.extent | 78 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
dc.subject | External diseases | en_US |
dc.subject | Lumpy Skin Disease (LSD) | en_US |
dc.subject | Foot and mouth(FMD) | en_US |
dc.subject | Infectious Bovine Keratoconjunctivitis (IBK) | en_US |
dc.subject | Developing countries | en_US |
dc.subject | Deep learning | en_US |
dc.subject | CattleSavior | en_US |
dc.subject.lcsh | Cognitive learning theory | |
dc.title | CattleSavior: towards implementing an advanced external disease detection system through deep learning | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
dc.description.degree | B.Sc. in Computer Science | |