0% Complete
Home
/
13th International Conference on Computer and Knowledge Engineering
Practical Implementation of Real-Time Waste Detection and Recycling based on Deep Learning for Delta Parallel Robot
Authors :
Hasan Jalali
1
Shaya Garjani
2
Ahmad Kalhor
3
Mehdi Tale Masouleh
4
Parisa Yousefi
5
1- School of Electrical and Computer Engineering, Human and Robot Interaction Laboratory, University of Tehran, Tehran, Iran
2- School of Electrical and Computer Engineering, Human and Robot Interaction Laboratory, University of Tehran, Tehran, Iran
3- School of Electrical and Computer Engineering, Human and Robot Interaction Laboratory, University of Tehran, Tehran, Iran
4- School of Electrical and Computer Engineering, Human and Robot Interaction Laboratory, University of Tehran, Tehran, Iran
5- School of Computer Engineering, Imam Reza International University, Mashhad, Iran
Keywords :
Deep Learning،Neural Networks،Waste Classification،Waste Detection،Delta Parallel Robot
Abstract :
Intelligent robots play an essential role in waste management and recycling due to their high speed and a wide variety of applications. In this paper, two methods for waste detection and accurate pick-and-place based on computer vision and neural networks are presented. The suggested methods have been put into practical application on a 3-DOF Delta parallel robot to show the accuracy and fastness of the foregoing method for real intelligence systems. The first method, Multi-Stage Detection, consists of two stages to detect the waste objects, namely, object localization and segmentation, and classification. The second method, known as One-Stage object detectors, such as YOLOv5, has the capability to simultaneously localize and classify the waste objects. The dataset utilized in this paper relies on the TrashNet dataset as its foundation. In order to improve the classification capabilities in the multi-stage method, a larger dataset was created by utilizing data augmentation. Also, for the one-stage method, a new multi-label dataset is constructed based on the TrashNet dataset. Additionally, the results of the experimental implementation were compared based on time and evaluation metrics for detection and classification. The ResNet50 model achieved the highest accuracy in the multi-stage method, with 99.31% accuracy. In the one-stage detection method, the YOLOv5x model achieved the best mAP (@IoU =0.75) of 97.4%, which outperformed the YOLOv5s model by 0.8 percent; however, the inference speed of the YOLOv5x in comparison with the YOLOv5s models was six times as slow. Therefore, the YOLOv5s model was employed in real-time online waste detection, which resulted in 82.1% mAP (@IoU = 0.5) after being trained on real images from the waste-sorting platform.
Papers List
List of archived papers
Adversarial Robustness Evaluation with Separation Index
Bahareh Kaviani Baghbaderani - Afsaneh Hasanebrahimi - Ahmad Kalhor - Reshad Hosseini
Deep Learning Based High-Resolution Edge Detection for Microwave Imaging using a Variational Autoencoder
Seyed Reza Razavi Pour - Leila Ahmadi - Amir Ahmad Shishegar
Farsi Optical Character Recognition Using a Transformer-based Model
Fatemeh Asadi Zeydabadi - Elham Shabaninia - Hossein Nezamabadi-pour - Melika Shojaee
Detecting Non-Spherical Clusters Using Modified CURE Algorithm
Arezou Safdari - Pedram Salehpour
A 2D-CNN Architecture for Improving the Classification Accuracy of an Electronic Nose with Different Sensor Positions
Hannaneh Mahdavi - Reza Goldoust - Saeideh Rahbarpour
Enhancing Vehicle Make and Model Recognition with 3D Attention Modules
Narges Semiromizadeh - Omid Nejati Manzari - Shahriar B. Shokouhi - Sattar Mirzakuchaki
Enhanced Principal-curve based Classifiers for Time-series Label Prediction
Seyed Aref Hakimzadeh - Koorush Ziarati
TrackMine: Topic Tracking in Model Mining using Genetic Algorithm
Mohammad Sajad Kasaei - Mohammadreza Sharbaf - Afsaneh Fatemi - Bahman Zamani
Brain Age Estimation with Twin Vision Transformer using Hippocampus Information Applicable to Alzheimer Dementia Diagnosis
Zahra Qodrati - Seyedeh Masoumeh Taji - Amirhossein Ghaemi - Habibollah Danyali - Kamran Kazemi - Alireza Ghaemi
Cross-project Defect Prediction with An Enhanced Transfer Boosting Algorithm
Nazgol Nikravesh - Mohammad Reza Keyvanpour
more
Samin Hamayesh - Version 41.7.6