Material Classification of Recyclable Containers Using 60 GHz Radar
Rather than sending used containers and materials to the landfill, recycling can help lower the human impact on the environment. However, manually sorting the mixture of incoming material can be both costly and potentially harmful to the person carrying out the task. In many cases, manual sorting could be replaced with automation, where a container is sorted by a machine, based on a classification of the container's material. In this paper, we propose a classification algorithm, using radar data, acquired with Acconeer's A121 60 GHz pulse coherent radar, for classifying liquid containers into one of the four classes metal, glass, plastic, or paper. The solution offers a cost-effective system with robust performance, able to predict the type of container with 98% accuracy.
Code (0)
등록된 구현이 없습니다.
Tasks
Material ClassificationSimilar Papers 제목 키워드 기반
Beyond Damage Assessment: Recyclable Material Detection in Aerial Disaster Imagery Using a Lightweight Patch-Based Framework
Nowadays, more and more disasters of different natures are appearing. Several disaster assessment approaches have been developed in order to identify damaged areas from aerial images. These damaged areas contain rich mat…
Waste Classification Algorithm
Waste sorting is a major environmental problem. Many have a hard time determining whether waste is organic, meaning food or natural material. Versus recyclable, which are able to be processed and used again. Computer Vis…
ClassificationRecyclable Waste Identification Using CNN Image Recognition and Gaussian Clustering
Waste recycling is an important way of saving energy and materials in the production process. In general cases recyclable objects are mixed with unrecyclable objects, which raises a need for identification and classifica…
ClassificationClusteringGeneral ClassificationImage Segmentation+2First Lessons Learned of an Artificial Intelligence Robotic System for Autonomous Coarse Waste Recycling Using Multispectral Imaging-Based Methods
Current disposal facilities for coarse-grained waste perform manual sorting of materials with heavy machinery. Large quantities of recyclable materials are lost to coarse waste, so more effective sorting processes must b…
Material Classificationobject-detectionObject DetectionRadar-based Materials Classification Using Deep Wavelet Scattering Transform: A Comparison of Centimeter vs. Millimeter Wave Units
Radar-based materials detection received significant attention in recent years for its potential inclusion in consumer and industrial applications like object recognition for grasping and manufacturing quality assurance …
ClassificationMaterial ClassificationObject Recognition