Date of Publication :10th February 2021

Abstract: In modern’s world , the data is generated on multi-folded and cross platform which can be used to understand and analyse different domains such as Floriculture , Agriculture , Finance etc. In all real time analysis of data where time , money , man-power is playing important roles to measure, pass judgement and react/answer in terms of Floriculture domain because the floriculture cultivation in world are increasing day by day The data generated from analysis which will be in the form of shape , colour , petals , size etc. Flower species and recognition system can provide unique approach for providing flower species analysis which could be a type of clutter of flowers , an area of farm where more flowers having issues like disease , water problem etc. In this process , Lots of data analyse , processed in real tome , provides good level of accuracy , precision , entropy etc. We can use deep learning approaches for detection flower species. This paper provides an overview of several pattern classification and detection mythologies/algorithms in the literature. The objective of the paper having companion with the comparison between different algorithms along with different types of datasets. The main goal is to provide an idea for several methods with different data and to find the many different approaches of the methods used for the detection of flowers using different scenarios

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