… The achieved results in terms of accuracy score about 63% for SVM and 73% for … classify
waste using CNN pre-trained models. The proposed system used F1 score, precision, accuracy…

… classification of solid waste items results in limited accuracy and increased error rate. Hence,
this paper concentrates on developing the optimized DL-based waste classification. The …

… The accuracy rate in the classification of plastic wastes was determined as 37% and 56.7%
in four-layer and five-layer DCNN architectures, respectively. In the research, organic …

… learning model for solid waste classification developed using … tool for accurate prediction
and management of solid waste in … accurate classification and management of municipal solid …

… all solid waste categories accurately. There is still a lack of large-scale databases for waste
classification on … CNN architecture developed for waste image classification consisting of five …

… an efficient municipal solid waste classification using a deep … images of waste products
with six classes of waste products. The … solid waste with improved accuracy. In the future, this …

… In this paper, rotation invariant bin detection and waste level classification is introduced. It
consists of bin detection, feature extraction and level classification methods that are accurate …

… to classify the waste bin level and estimate the amount of waste inside … The classification
accuracy measure is guided by the … % classification accuracy that is validating the classification …

… Recent advancements in deep learning have made a breakthrough by improving the
accuracy in the area of image classification. The deep learning model passes queries through …

… the detection and classification of multi-target solid waste with high accuracy. The experiment
… can effectively reduce the training time of model, and the model accuracy rate is higher. …