AIMC Topic: Image Processing, Computer-Assisted

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HOReID: Deep High-Order Mapping Enhances Pose Alignment for Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Despite the remarkable progress in recent years, person Re-Identification (ReID) approaches frequently fail in cases where the semantic body parts are misaligned between the detected human boxes. To mitigate such cases, we propose a novel High-Order ...

Complementary Pseudo Labels for Unsupervised Domain Adaptation On Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In recent years, supervised person re-identification (re-ID) models have received increasing studies. However, these models trained on the source domain always suffer dramatic performance drop when tested on an unseen domain. Existing methods are pri...

An Accurate and Lightweight Method for Human Body Image Super-Resolution.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we propose a new method to super-resolve low resolution human body images by learning efficient multi-scale features and exploiting useful human body prior. Specifically, we propose a lightweight multi-scale block (LMSB) as basic modul...

Giant Panda Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The lack of automatic tools to identify giant panda makes it hard to keep track of and manage giant pandas in wildlife conservation missions. In this paper, we introduce a new Giant Panda Identification (GPID) task, which aims to identify each indivi...

Condition-Aware Comparison Scheme for Gait Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
As an important and challenging problem, gait recognition has gained considerable attention. It suffers from confounding conditions, that is, it is sensitive to camera views, dressing types and so on. Interestingly, it is observed that, under differe...

Introducing Swish and Parallelized Blind Removal Improves the Performance of a Convolutional Neural Network in Denoising MR Images.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: To improve the performance of a denoising convolutional neural network (DnCNN) and to make it applicable to images with inhomogeneous noise, a refinement involving an activation function (AF) and an application of the refined method for inho...

Real-time volumetric reconstruction of biological dynamics with light-field microscopy and deep learning.

Nature methods
Light-field microscopy has emerged as a technique of choice for high-speed volumetric imaging of fast biological processes. However, artifacts, nonuniform resolution and a slow reconstruction speed have limited its full capabilities for in toto extra...

Deep learning-based metal artefact reduction in PET/CT imaging.

European radiology
OBJECTIVES: The susceptibility of CT imaging to metallic objects gives rise to strong streak artefacts and skewed information about the attenuation medium around the metallic implants. This metal-induced artefact in CT images leads to inaccurate atte...

SAM-GAN: Self-Attention supporting Multi-stage Generative Adversarial Networks for text-to-image synthesis.

Neural networks : the official journal of the International Neural Network Society
Synthesizing photo-realistic images based on text descriptions is a challenging task in the field of computer vision. Although generative adversarial networks have made significant breakthroughs in this task, they still face huge challenges in genera...

Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events.

Scientific reports
Radiomics, quantitative feature extraction from radiological images, can improve disease diagnosis and prognostication. However, radiomic features are susceptible to image acquisition and segmentation variability. Ideally, only features robust to the...