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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...
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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...
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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...
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04/03/2023
Grand Challenge On Detecting Cheapfakes
Cheapfake is a recently coined term that encompasses non-AI ("cheap") ma...
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02/02/2023
Conditional expectation for missing data imputation
Missing data is common in datasets retrieved in various areas, such as m...
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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...
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07/29/2022
ACM Multimedia Grand Challenge on Detecting Cheapfakes
Cheapfake is a recently coined term that encompasses non-AI (“cheap”) ma...
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07/27/2022
Towards the Neuroevolution of Low-level Artificial General Intelligence
In this work, we argue that the search for Artificial General Intelligen...
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06/22/2022
Video Analytics in Elite Soccer: A Distributed Computing Perspective
Ubiquitous sensors and Internet of Things (IoT) technologies have revolu...
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05/30/2022
Principle Components Analysis based frameworks for efficient missing data imputation algorithms
Missing data is a commonly occurring problem in practice, and imputation...
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03/03/2022
Parallel feature selection based on the trace ratio criterion
The growth of data today poses a challenge in management and inference. ...
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11/20/2021
PAANet: Progressive Alternating Attention for Automatic Medical Image Segmentation
Medical image segmentation can provide detailed information for clinical...
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09/02/2021
Artificial Intelligence in Dry Eye Disease
Dry eye disease (DED) has a prevalence of between 5 and 50%, depending o...
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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 ...
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07/01/2021
DivergentNets: Medical Image Segmentation by Network Ensemble
Detection of colon polyps has become a trending topic in the intersectin...
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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...
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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 ...
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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...
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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...
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04/22/2021
NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopy
Deep learning in gastrointestinal endoscopy can assist to improve clinic...
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03/31/2021
FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation
With the increase in available large clinical and experimental datasets,...
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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...
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12/30/2020
DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation
Colonoscopy is the gold standard for examination and detection of colore...
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12/30/2020
Medico Multimedia Task at MediaEval 2020: Automatic Polyp Segmentation
Colorectal cancer is the third most common cause of cancer worldwide. Ac...
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12/14/2020
Pyramid-Focus-Augmentation: Medical Image Segmentation with Step-Wise Focus
Segmentation of findings in the gastrointestinal tract is a challenging ...
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11/15/2020
Real-Time Polyp Detection, Localisation and Segmentation in Colonoscopy Using Deep Learning
Computer-aided detection, localisation, and segmentation methods can hel...
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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 ...
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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) ...
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03/23/2020
Robust Medical Instrument Segmentation Challenge 2019
Intraoperative tracking of laparoscopic instruments is often a prerequis...
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11/16/2019
Kvasir-SEG: A Segmented Polyp Dataset
Pixel-wise image segmentation is a highly demanding task in medical-imag...
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11/16/2019
ResUNet++: An Advanced Architecture for Medical Image Segmentation
Accurate computer-aided polyp detection and segmentation during colonosc...
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11/08/2019
Extracting temporal features into a spatial domain using autoencoders for sperm video analysis
In this paper, we present a two-step deep learning method that is used t...
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11/08/2019
Stacked dense optical flows and dropout layers to predict sperm motility and morphology
In this paper, we analyse two deep learning methods to predict sperm mot...
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10/31/2018