IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jul 4, 2024
Combining dual-energy computed tomography (DECT) with positron emission tomography (PET) offers many potential clinical applications but typically requires expensive hardware upgrades or increases radiation doses on PET/CT scanners due to an extra X-...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 16, 2024
Accurate segmentation of lesions is crucial for diagnosis and treatment of early esophageal cancer (EEC). However, neither traditional nor deep learning-based methods up to today can meet the clinical requirements, with the mean Dice score - the most...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 10, 2024
This research investigates the potential of in vivo learning to enhance visual representation learning for image-based person re-identification (re-ID). Compared to traditional self-supervised learning (which require external data), the introduced in...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Nov 15, 2023
Facial expression editing has attracted increasing attention with the advance of deep neural networks in recent years. However, most existing methods suffer from compromised editing fidelity and limited usability as they either ignore pose variations...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Aug 8, 2023
There are demographic biases present in current facial recognition (FR) models. To measure these biases across different ethnic and gender subgroups, we introduce our Balanced Faces in the Wild (BFW) dataset. This dataset allows for the characterizat...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jul 14, 2023
Modern deep neural networks have made numerous breakthroughs in real-world applications, yet they remain vulnerable to some imperceptible adversarial perturbations. These tailored perturbations can severely disrupt the inference of current deep learn...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jun 29, 2023
Uncertainty is inherent in machine learning methods, especially those for camouflaged object detection aiming to finely segment the objects concealed in background. The strong enquote center bias of the training dataset leads to models of poor genera...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jun 23, 2023
Intra prediction is a crucial part of video compression, which utilizes local information in images to eliminate spatial redundancy. As the state-of-the-art video coding standard, Versatile Video Coding (H.266/VVC) employs multiple directional predic...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Nov 23, 2022
Semi-supervised domain adaptation (SSDA) is quite a challenging problem requiring methods to overcome both 1) overfitting towards poorly annotated data and 2) distribution shift across domains. Unfortunately, a simple combination of domain adaptation...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Nov 14, 2022
Person detection has attracted great attention in the computer vision area and is an imperative element in human-centric computer vision. Although the predictive performances of person detection networks have been improved dramatically, they are vuln...