WasteNet Archives - Recycleye

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31.01.22

Modelling of a modern MRF

Paloma’s paper has a dual focus on two of the challenges faced by MRFs today: The challenges associated with efficiency, waste composition variation and waste sampling methods….

WasteNet WasteNet: Waste Management

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18.11.21

Single Shot 2D Image to 3D Model

This research consists of 2 papers offering differing reconstruction approaches to obtain high accuracy inferences of 3D structures with textures from 2D single shot images….

WasteNet WasteNet: Machine Learning

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15.02.21

Decentralised and Digitised Mini Material Recovery Facilities

This research explores the disruption of centralised waste facilities to accommodate a decentralised model, known as the mini-MRF, that is capable of extracting more value out of waste streams….

WasteNet WasteNet: Waste Management

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04.02.21

Deep Learning: Unsupervised Domain Adaptation

The goal of this WasteNet series is to engineer a Deep Learning model that will focus on UDA for the instance segmentation task. As such, there are only two other approaches that are addressing this. …

WasteNet WasteNet: Machine Learning

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01.02.21

Regulated Bans in Waste Management

Amandine looks at how we can form healthier consumer habits and increased recycling rates by enforcing regulations around complex materials….

WasteNet

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01.02.21

An Application of Machine Learning for Brand-Level Waste Management

Computer vision for brand-level logo detection of waste in real-time was tested. The brand recognition of waste items can be used to increase the granularity of the waste characterisation, simultaneously providing information to improve mass measurements. …

WasteNet

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04.01.21

Recycleye Bin: A Human-in-the-Loop Approach to Computer Vision Waste Disposal

Studies have shown that the rate of recycling amongst individuals can be increased by correcting mistakes. …

WasteNet WasteNet: Machine Learning

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28.12.20

Instance Segmentation of Novel Objects in a Conveyer Setting

The advancements in deep learning have enabled rapid growth of computer vision capabilities. However, in order to achieve successful results, it requires a heavy reliance on the availability of large labelled datasets….

WasteNet WasteNet: Machine Learning

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04.12.20