ISSN 0975-3583
 

Journal of Cardiovascular Disease Research



    AN ADVANCED IMAGE AND MACHINE LEANING BASED PEST CONTROL FOR FUTURE CULTIVATIONS


    Dr B Ravi Prasad, K Abdul Basith
    JCDR. 2021: 670-677

    Abstract

    Agriculture is essential to any country’s economy because it just only feeds its people but also produces a large amount of goods and services. Pests like insects & rodents can wreak havoc on plants & are hence extremely perilous to farmers' development of the crop as a whole. Early tormentor from the beginning Prevention could be a huge obstacle for farmers. Sector. The most effective method of controlling the aggressor the usage of pesticides is a major cause of illness. On the other hand, the usage of pesticides can have negative effects on Despite their numbers, flora and animals still interact strategy that uses artificial intelligence to identify bullies at an early stage. The Image processing using digital methods widely utilised in the field of agricultural research, and beautiful vantage point, especially from under the plant field of security, the results of which are planted crops management. In this article, we explore a novel variant of the technology for early detection of pests. Depictions of leaves Bugs don't run in the family via means of a photographic camera. Certificate of completion. An automatic system, one that might not the presence of a pestilence can be detected by inspecting the crops. Yet it can also be used to categorise the different kinds of plant-destroying insects. Terrorists use the YOLO algorithmic rule. Machine learning, detection, & Support Vector Machine used for sorting images with and while not a single pest tested any of the visual choices.

    Description

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    Volume & Issue

    Volume 12 Issue 2

    Keywords