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Quality control on production lines with Computer Vision and TinyML
This repository includes a jupyter notebook that presents a complete pipeline for: EDA on image data Data preparation and augmentation Deep learning (CNN) models development for image classification with TensorFlow Models evaluation Model interpret...
Neighborhood Contrastive Learning for Novel Class Discovery
A holistic learning framework for Novel Class Discovery (NCD), which adopts contrastive learning to learn discriminate features with both the labeled and unlabeled data. The Neighborhood Contrastive Learning (NCL) framework effectively leverages the local...
IEP-GAN: Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer
PyTorch implementation of Intrinsic-Extrinsic Preserved Generative Adversarial Network (IEP-GAN) for both intrinsic (i.e., shape) and extrinsic (i.e., pose) information preservation. Extrinsically, a co-occurrence discriminator is used to capture the stru...
Efficient Training of Visual Transformers with Small Datasets
A tool to allow Visual Transformers (VTs) to learn spatial relations within an image making the VT training much more robust when training data is scarce. The tool can be used jointly with the standard (supervised) training and it does not depend on speci...
Differentiable SVD
As the backward algorithm of SVD is prone to have numerical instability, we implement a variety of end-to-end SVD methods by manipulating the backward algortihms in this repository. They include: - SVD-Pad'e: use Pad'e approximants to closely approximate...
Ship energy system design optimisation
Optimisation of the design and operation of ship energy systems in terms of energy efficiency and lifecycle costs
I-NERGY Transfer Learning Wizard
I-NERGY Transfer Learning Wizard is an application designed for novice data analysts to analyse energy data and develop machine learning (ML) models based on the Transfer Learning method.