Michael A. Riegler

research

∙ 07/16/2023

GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection

Integrating real-time artificial intelligence (AI) systems in clinical p...

0 Debesh Jha, et al. ∙

research

∙ 05/10/2023

Correlation visualization under missing values: a comparison between imputation and direct parameter estimation methods

Correlation matrix visualization is essential for understanding the rela...

0 Nhat-Hao Pham, et al. ∙

research

∙ 05/10/2023

Blockwise Principal Component Analysis for monotone missing data imputation and dimensionality reduction

Monotone missing data is a common problem in data analysis. However, imp...

0 Tu T. Do, et al. ∙

research

∙ 02/02/2023

Conditional expectation for missing data imputation

Missing data is common in datasets retrieved in various areas, such as m...

0 Mai Anh Vu, et al. ∙

research

∙ 10/11/2022

Combining datasets to increase the number of samples and improve model fitting

For many use cases, combining information from different datasets can be...

0 Thu Nguyen, et al. ∙

research

∙ 07/27/2022

Towards the Neuroevolution of Low-level Artificial General Intelligence

In this work, we argue that the search for Artificial General Intelligen...

7 Sidney Pontes-Filho, et al. ∙

research

∙ 06/22/2022

Video Analytics in Elite Soccer: A Distributed Computing Perspective

Ubiquitous sensors and Internet of Things (IoT) technologies have revolu...

0 Debesh Jha, et al. ∙

research

∙ 11/22/2021

Visual Sentiment Analysis: A Natural DisasterUse-case Task at MediaEval 2021

The Visual Sentiment Analysis task is being offered for the first time a...

0 Syed Zohaib Hassan, et al. ∙

research

∙ 11/20/2021

PAANet: Progressive Alternating Attention for Automatic Medical Image Segmentation

Medical image segmentation can provide detailed information for clinical...

9 Abhishek Srivastava, et al. ∙

research

∙ 09/02/2021

Artificial Intelligence in Dry Eye Disease

Dry eye disease (DED) has a prevalence of between 5 and 50%, depending o...

18 Andrea M. Storås, et al. ∙

research

∙ 07/26/2021

A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation

Colonoscopy is considered the gold standard for detection of colorectal ...

14 Debesh Jha, et al. ∙

research

∙ 07/01/2021

DivergentNets: Medical Image Segmentation by Network Ensemble

Detection of colon polyps has become a trending topic in the intersectin...

0 Vajira Thambawita, et al. ∙

research

∙ 06/29/2021

SinGAN-Seg: Synthetic Training Data Generation for Medical Image Segmentation

Processing medical data to find abnormalities is a time-consuming and co...

53 Vajira Thambawita, et al. ∙

research

∙ 06/08/2021

PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment

Polyps in the colon are widely known as cancer precursors identified by ...

20 Sharib Ali, et al. ∙

research

∙ 06/06/2021

Few-shot segmentation of medical images based on meta-learning with implicit gradients

Classical supervised methods commonly used often suffer from the require...

19 Rabindra Khadga, et al. ∙

research

∙ 05/16/2021

MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation

Methods based on convolutional neural networks have improved the perform...

8 Abhishek Srivastava, et al. ∙

research

∙ 04/22/2021

NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopy

Deep learning in gastrointestinal endoscopy can assist to improve clinic...

14 Debesh Jha, et al. ∙

research

∙ 03/31/2021

FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation

With the increase in available large clinical and experimental datasets,...

11 Nikhil Kumar Tomar, et al. ∙

research

∙ 01/06/2021

LightLayers: Parameter Efficient Dense and Convolutional Layers for Image Classification

Deep Neural Networks (DNNs) have become the de-facto standard in compute...

12 Debesh Jha, et al. ∙

research

∙ 12/30/2020

DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation

Colonoscopy is the gold standard for examination and detection of colore...

32 Nikhil Kumar Tomar, et al. ∙

research

∙ 12/30/2020

Medico Multimedia Task at MediaEval 2020: Automatic Polyp Segmentation

Colorectal cancer is the third most common cause of cancer worldwide. Ac...

13 Debesh Jha, et al. ∙

research

∙ 12/14/2020

Pyramid-Focus-Augmentation: Medical Image Segmentation with Step-Wise Focus

Segmentation of findings in the gastrointestinal tract is a challenging ...

0 Vajira Thambawita, et al. ∙

research

∙ 11/15/2020

Real-Time Polyp Detection, Localisation and Segmentation in Colonoscopy Using Deep Learning

Computer-aided detection, localisation, and segmentation methods can hel...

17 Debesh Jha, et al. ∙

research

∙ 06/08/2020

DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation

Semantic image segmentation is the process of labeling each pixel of an ...

64 Debesh Jha, et al. ∙

research

∙ 05/08/2020

An Extensive Study on Cross-Dataset Bias and Evaluation Metrics Interpretation for Machine Learning applied to Gastrointestinal Tract Abnormality Classification

Precise and efficient automated identification of Gastrointestinal (GI) ...

11 Vajira Thambawita, et al. ∙

research

∙ 04/27/2020

Efficient Quantile Tracking Using an Oracle

For incremental quantile estimators the step size and possibly other tun...

0 Hugo L. Hammer, et al. ∙

research

∙ 03/23/2020

Robust Medical Instrument Segmentation Challenge 2019

Intraoperative tracking of laparoscopic instruments is often a prerequis...

13 Tobias Ross, et al. ∙

research

∙ 11/16/2019

Kvasir-SEG: A Segmented Polyp Dataset

Pixel-wise image segmentation is a highly demanding task in medical-imag...

0 Debesh Jha, et al. ∙

research

∙ 11/16/2019

ResUNet++: An Advanced Architecture for Medical Image Segmentation

Accurate computer-aided polyp detection and segmentation during colonosc...

0 Debesh Jha, et al. ∙

research

∙ 10/29/2019

Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction

Methods for automatic analysis of clinical data are usually targeted tow...

37 Steven A. Hicks, et al. ∙

Michael A. Riegler

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