A multi-label image classification is used to classify an input image into one of the labeled classes of the dataset. Authors are trying to build an image classification model to classify solid waste into different categories to make the process of recycling automated and efficient. The objective...
We demonstrate a high accuracy of the classification approach to perform the task of plastic waste segregation by validation on the WaDaBa database that contain images of such plastic wastes (Bobulski and Piatkowski in Pet waste classification method and plastic waste database-wadaba. In: ...
describes the multi-label waste image dataset, the construction of the YOLO-WASTE model based on transfer learning, and the evaluation index of the model Section 4. introduces the experimental results and model evaluation results. The paper closes with discussion and conclusions in Section 5 and ...
However, traditional manual methods for waste segregation are time-consuming, labour-intensive, and prone to errors. Numerous artificial intelligence applications in waste management can greatly benefit from the use of technology to streamline and improve the waste detection and classification process. ...
Segregation techniques should continue to remain the same and wastes related with COVID-19 should no differently treated/disposed like other HCWs. The following are some of the recommendations of WHO to treat/dispose COVID-19 wastes (World Health Organization, 2020). Lot of attempts has been ...
Similarly, we complement the HDD dataset with a new dataset containing phone parts. By adding a new task, we represent the variety of devices the robot has to deal with. Both these additions contribute to increasing the quality of the learning data. We then perform an extensive evaluation ...
, the correctly identified rate was 90.5% for using the “BG + 3D” image that results from overwriting the third channel of the BGR color image with the 3D image fusing density information of the digital device under “fine-tuning” of the VGG16 pre-trained by the ImageNet dataset....
Developing an intelligent infrastructure with sensor-based technology for adequate garbage segregation, collection, and recycling. In summary, smart cities have emerged as a global model that prioritizes sustainability. With the help of computing, networking, and data management advancements, institutions ...
On-site waste segregation is a powerful WM method that facilitates the construction team to maximise the waste recovery potential [105]. Nevertheless, handling these waste materials is time-consuming, cost ineffective, and requires manual work [106]. To overcome these issues, autonomous robots are ...
With segregation of wastes at site, e.g. for recycling or reuse, the collection cost reduces dramatically when compared to non-separated wastes (Lombrano, 2009). Hence, forecasting the MSW generation rates will be helpful for the development of a municipal solid waste storage, collection and ...