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dc.contributor.advisorMukta, Jannatun Noor
dc.contributor.advisorRahman, Rafeed
dc.contributor.authorDas, Rantu
dc.contributor.authorSinha, Yousuf
dc.contributor.authorSahid, Sohidul Haque
dc.contributor.authorKar, Dipta Dipayan
dc.contributor.authorShaheen, Shahidul Haque
dc.date.accessioned2024-08-19T05:53:04Z
dc.date.available2024-08-19T05:53:04Z
dc.date.copyright2023
dc.date.issued2023-08
dc.identifier.otherID 20301343
dc.identifier.otherID 20301432
dc.identifier.otherID 20301403
dc.identifier.otherID 20301414
dc.identifier.otherID 19201033
dc.identifier.urihttp://hdl.handle.net/10361/23792
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes 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.statementofresponsibilityRantu Das
dc.description.statementofresponsibilityYousuf Sinha
dc.description.statementofresponsibilitySohidul Haque Sahid
dc.description.statementofresponsibilityDipta Dipayan Kar
dc.description.statementofresponsibilityShahidul Haque Shaheen
dc.format.extent78 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac 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.subjectExternal diseasesen_US
dc.subjectLumpy Skin Disease (LSD)en_US
dc.subjectFoot and mouth(FMD)en_US
dc.subjectInfectious Bovine Keratoconjunctivitis (IBK)en_US
dc.subjectDeveloping countriesen_US
dc.subjectDeep learningen_US
dc.subjectCattleSavioren_US
dc.subject.lcshCognitive learning theory
dc.titleCattleSavior: towards implementing an advanced external disease detection system through deep learningen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB.Sc. in Computer Science


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