Machine learning approach for detection and classification of biomedical waste objects

This paper mostly focuses on real-time detection and classification of biomedical waste objects. Traditional methods for detecting the objects like biomedical waste objects in machine learning are substituted by recent technology of object detection methods in deep learning by building Convolutional...

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Hauptverfasser: Mohite, Trupti, Sankpal, Swati
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:This paper mostly focuses on real-time detection and classification of biomedical waste objects. Traditional methods for detecting the objects like biomedical waste objects in machine learning are substituted by recent technology of object detection methods in deep learning by building Convolutional Neural Network (CNN) which is nothing but the components of deep learning. This paper proposes a deep learning approach for object detection of biomedical waste material by evaluating the TensorFlow object detection API, which can used for real time application, this biomedical object detection API further we can used for automate the biomedical waste segregation system, this proposed system has been trained using more than 500 images for each type of biomedical waste object. Tensorflow is useful and easy to object detection that can form powerful image recognition software, in this proposed work we are using Faster R-CNN algorithm for developing this object detection process.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0175687