Plant Disease Detection and Classification with Deep Learning

Usecase in Biotechnology Data Intelligence

Detecting the plant diseases at the early stages is beneficial as it saves time, effort, and money. Preventing the wastage of finances,  along with other resources, and achieving healthier crop production by addressing the pathogen-resistant problem and weakening the negative effects of climate change becomes crucial. For detecting the diseases in plants, an automated disease detection technique will be beneficial. 

In this study, we attempted to perform an image-based detection and classification of the plant diseases by applying Deep Learning algorithms and Computer Vision. 

Deep Learning models are the most accurate and precise models for the detection of plant disease. The leaves from the infected plant are collected and labeled with the disease type and the processing of this image of the leaf is performed. 

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About Qualetics Data Machines

Data Analytics and Artificial Intelligence is growing to be an ubiquitous need in the modern enterprise ecosystem. The need for Analytics is ranging from basic Descriptive and Diagnostic Analytics to advanced Predictive, Prescriptive and Cognitive Analytics.  However, the barrier of entry is high due to expensive infrastructure and highly skilled resource requirements.

Qualetics Data Machines Inc. aims to eliminate this barrier by introducing a product that makes it easy for businesses to embrace data science and gain data intelligence.

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