37 citations · 44 across the 6 of their papers we have counts for
6 papers
AMF: Adaptable Weighting Fusion with Multiple Fine-tuning for Image Classification
Xuyang Shen, Jo Plested, Sabrina Caldwell +2
Fine-tuning is widely applied in image classification tasks as a transfer learning approach. It re-uses the knowledge from a source task to learn and obtain a high performance in t…
Deep transfer learning for image classification: a survey
Jo Plested, Musa Phiri, Tom Gedeon
Deep neural networks such as convolutional neural networks (CNNs) and transformers have achieved many successes in image classification in recent years. It has been consistently de…
Feature Selection on Thermal-stress Dataset
Xuyang Shen, Jo Plested, Tom Gedeon
Physical symptoms caused by high stress commonly happen in our daily lives, leading to the importance of stress recognition systems. This study aims to improve stress classificatio…
Non-binary deep transfer learning for image classification
Jo Plested, Xuyang Shen, Tom Gedeon
The current standard for a variety of computer vision tasks using smaller numbers of labelled training examples is to fine-tune from weights pre-trained on a large image classifica…
Exploring Biases and Prejudice of Facial Synthesis via Semantic Latent Space
Xuyang Shen, Jo Plested, Sabrina Caldwell +1
Deep learning (DL) models are widely used to provide a more convenient and smarter life. However, biased algorithms will negatively influence us. For instance, groups targeted by b…
Pairwise-GAN: Pose-based View Synthesis through Pair-Wise Training
Xuyang Shen, Jo Plested, Yue Yao +1
Three-dimensional face reconstruction is one of the popular applications in computer vision. However, even state-of-the-art models still require frontal face as inputs, which restr…