Výsledky vyhledávání - "Monica M. Kabemba"

Developing an automatic identification and early warning and monitoring web based system of fall army worm based on machine learning in developing countries

Autor: Mayumbo Nyirenda, Monica M. Kabemba, P. O. Y. Nkunika, Francis Chulu, Simon Hawatichke Chiwamba, Jackson Phiri

Publikováno v: Zambia ICT Journal. 3:13-20

To combat the fall Army worm (FAW-Spodoptera frugiperda) pest which has a negative impact on world food security, there is need to come up with methods that can be used alongside conventional methods of spraying. Therefore this paper proposes a machi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b6fc5ac2e36029eea5f5c635ad82f840
https://doi.org/10.33260/zictjournal.v3i1.71

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Technological Paradox of Hackers Begetting Hackers: A Case of Ethical and Unethical Hackers and their Subtle Tools

Autor: Monica M. Kabemba, Raphael Banda, Jackson Phiri, Mayumbo Nyirenda

Publikováno v: Zambia ICT Journal. 3:40-51

Computer crimes have been in existence for a long time now and hacking is just another way or tool that hackers are now using to perpetrate crime in different form. Hackers Beget Ethical Hackers. A number of people have suffered the consequences of h

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::994c3b1c6e5c63ef6a45e615d4897d9a
https://doi.org/10.33260/zictjournal.v3i1.74

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Machine Learning Algorithms for automated Image Capture and Identification of Fall Armyworm (FAW) Moths

Autor: Jackson Phiri, Simon Hawatichke Chiwamba, Monica M. Kabemba, Mayumbo Nyirenda, Philip O. Y. Nkunika, Philemon H. Sohati

Publikováno v: Zambia ICT Journal. 3:1-4

Automated entomology is one of the field that has received a fair attention from the computer scientists and its support disciplines. This can further be confirmed by the recent attention that the Fall Armyworm (FAW) (Spodoptera frugiperda) has recei

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7814701e0be7af62869dbc9f7591663d
https://doi.org/10.33260/zictjournal.v3i1.69

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A convolutional neural network for automatic identification and classification of Fall Army Worm Moth

Autor: Philemon H. Sohati, Mayumbo Nyirenda, Monica M. Kabemba, P. O. Y. Nkunika, Jackson Phiri, Francis Chulu

Publikováno v: Scopus-Elsevier

To combat the problem caused by the Fall Army Worm in the country there is a need to come up with robust early warning and monitoring systems as the current manual system is labor intensive and time consuming. The automation of the identification and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03deea62d12126b9448446d8551485ca
http://www.scopus.com/inward/record.url?eid=2-s2.0-85070083253&partnerID=MN8TOARS

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