Search Results for author:
Found 18 papers, 3 papers with code
End-to-end Dynamic Matching Network for Multi-view Multi-person 3d Pose Estimation
To address this phenomenon, we propose a novel end-to-end training scheme that brings the three separate modules into a single model.
Improving Colorectal Cancer Screening and Risk Assessment through Predictive Modeling on Medical Images and Records
The evolution of digital pathology and recent advancements in deep learning provide a unique opportunity to investigate the added benefits of including the additional medical record information and automatic processing of pathology slides using computer vision techniques in the calculation of future CRC risk.
MindShot: Brain Decoding Framework Using Only One Image
Brain decoding, which aims at reconstructing visual stimuli from brain signals, primarily utilizing functional magnetic resonance imaging (fMRI), has recently made positive progress.
Automatic laminectomy cutting plane planning based on artificial intelligence in robot assisted laminectomy surgery
Results: In the first stage, the average localization error of the SPU-Net algorithm for the seven key points was 0. 65mm.
GlanceSeg: Real-time microaneurysm lesion segmentation with gaze-map-guided foundation model for early detection of diabetic retinopathy
In this work, we propose a human-in-the-loop, label-free early DR diagnosis framework called GlanceSeg, based on SAM.
VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence
To be commensurate with this capacity, in addition to the real data used for pre-training, we also generated and leveraged synthetic ophthalmic imaging data.
A Visual Interpretation-Based Self-Improved Classification System Using Virtual Adversarial Training
The successful application of large pre-trained models such as BERT in natural language processing has attracted more attention from researchers.
Mutually Guided Few-shot Learning for Relational Triple Extraction
Specifically, our method consists of an entity-guided relation proto-decoder to classify the relations firstly and a relation-guided entity proto-decoder to extract entities based on the classified relations.
Masked Pre-Training of Transformers for Histology Image Analysis
However, due to the large number of model parameters and limited labeled data, applying transformer models to WSIs remains challenging.
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results
The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection.
MHAttnSurv: Multi-Head Attention for Survival Prediction Using Whole-Slide Pathology Images
In pathology, whole-slide images (WSI) based survival prediction has attracted increasing interest.
Unsupervised clothing change adaptive person ReID
We developer a purely unsupervised clothing change person ReID pipeline with person sync augmentation operation and same person feature restriction.
Resolution-invariant Person ReID Based on Feature Transformation and Self-weighted Attention
In this paper, we propose a novel two-stream network with a lightweight resolution association ReID feature transformation (RAFT) module and a self-weighted attention (SWA) ReID module to evaluate features under different resolutions.
RGB-IR Cross-modality Person ReID based on Teacher-Student GAN Model
To solve this challenge, we proposed a Teacher-Student GAN model (TS-GAN) to adopt different domains and guide the ReID backbone to learn better ReID information.
Illumination adaptive person reid based on teacher-student model and adversarial training
Most existing works in Person Re-identification (ReID) focus on settings where illumination either is kept the same or has very little fluctuation.
GAN-based Gaussian Mixture Model Responsibility Learning
Instead of defining p(x|k, θ) explicitly, we devised a modified GAN to allow us to define the distribution using p(z|k, θ), where z is the corresponding latent representation of x, as well as p(k|x, θ) through an additional classification network which is trained with the GAN in an “end-to-end” fashion.
Magnitude Bounded Matrix Factorisation for Recommender Systems
Low rank matrix factorisation is often used in recommender systems as a way of extracting latent features.
Relative Pairwise Relationship Constrained Non-negative Matrix Factorisation
Non-negative Matrix Factorisation (NMF) has been extensively used in machine learning and data analytics applications.
