Add to ORKGA method for sorting plastic waste is developed. This method pretends to classify polymers by types using infrared spectrum despite the wavelength range of the data acquisition experiment. Thus, plastic spectrums collected in NIR or MIR wavelength ranges could be classified applying the same method.Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructur
The aim of this work was to recognize different polymer flakes from mixed plastic waste through an i...
Mismanagement of plastic waste globally has resulted in a multitude of environmental issues, which c...
Valorisation of the urban plastic waste in high-quality recyclates is an imperative challenge in the...
We present a combination of convolutional neural network (CNN) framework and fast MIR (mid-infrared ...
We present a convolutional neural network (CNN) framework for classifying different types of plastic...
Nowadays, plastic usage and production is increasing leading to an augmentation in waste generation ...
This work contributes to the recycling of technical black plastic particles, for example from the au...
The classification of plastic waste before recycling is of great significance to achieve effective r...
Plastic is widely used material all over the world. Use of plastic creates waste which is necessary ...
Plastic waste issues emerged from the build-up of plastics that negatively impacts the environment. ...
Whereas plastics are a group of the most useful materials, widely used in all walks of life, the pla...
Plastic waste management is a challenge for the whole world. Manual sorting of garbage is a difficul...
International audienceOne of the major limitations in polymer recycling is their sorting as they are...
Aim of this work is to recognize different waste polymers through an innovative strategy based on a ...
Non-destructive spectroscopic analysis combined with machine learning rapidly provides information o...
The aim of this work was to recognize different polymer flakes from mixed plastic waste through an i...
Mismanagement of plastic waste globally has resulted in a multitude of environmental issues, which c...
Valorisation of the urban plastic waste in high-quality recyclates is an imperative challenge in the...
We present a combination of convolutional neural network (CNN) framework and fast MIR (mid-infrared ...
We present a convolutional neural network (CNN) framework for classifying different types of plastic...
Nowadays, plastic usage and production is increasing leading to an augmentation in waste generation ...
This work contributes to the recycling of technical black plastic particles, for example from the au...
The classification of plastic waste before recycling is of great significance to achieve effective r...
Plastic is widely used material all over the world. Use of plastic creates waste which is necessary ...
Plastic waste issues emerged from the build-up of plastics that negatively impacts the environment. ...
Whereas plastics are a group of the most useful materials, widely used in all walks of life, the pla...
Plastic waste management is a challenge for the whole world. Manual sorting of garbage is a difficul...
International audienceOne of the major limitations in polymer recycling is their sorting as they are...
Aim of this work is to recognize different waste polymers through an innovative strategy based on a ...
Non-destructive spectroscopic analysis combined with machine learning rapidly provides information o...
The aim of this work was to recognize different polymer flakes from mixed plastic waste through an i...
Mismanagement of plastic waste globally has resulted in a multitude of environmental issues, which c...
Valorisation of the urban plastic waste in high-quality recyclates is an imperative challenge in the...