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….
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. …
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. …
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. …
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….
A Generative Adversarial Network (GAN) to Generate Transparent Objects
The research conducted uses a technique which creates synthetic data using a general adversarial network to generate transparent objects….