Search Results for author:
Found 7 papers, 4 papers with code
Multi-scale self-guided attention for medical image segmentation
In this paper we attempt to overcome these limitations with the proposed architecture, by capturing richer contextual dependencies based on the use of guided self-attention mechanisms.
Ranked #1 on
Medical Image Segmentation
on HSVM
DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images
In recent years, deep learning (DL) has shown great potential in the field of dermatological image analysis.
MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds
Unsupervised domain adaptation (UDA) addresses the problem of distribution shift between the unlabelled target domain and labelled source domain.
Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields
We propose a novel approach for representing anatomical trees using INR, while also capturing the distribution of a set of trees via denoising diffusion in the space of INRs.
GA-GAN: CT reconstruction from Biplanar DRRs using GAN with Guided Attention
We try to improve the visual image quality of the CT reconstruction using Guided Attention based GANs (GA-GAN).
NTIRE 2020 Challenge on Image Demoireing: Methods and Results
Track 1 targeted the single image demoireing problem, which seeks to remove moire patterns from a single image.
Deep Learning based Dimple Segmentation for Quantitative Fractography
In this work, we try to address the challenging problem of dimple detection and segmentation in Titanium alloys using machine learning methods, especially neural networks.
