research
∙
02/13/2023
CholecTriplet2022: Show me a tool and tell me the triplet – an endoscopic vision challenge for surgical action triplet detection
Formalizing surgical activities as triplets of the used instruments, act...
share
research
∙
09/30/2022
Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks
Convolutional Neural Networks have played a significant role in various ...
research
∙
04/10/2022
CholecTriplet2021: A benchmark challenge for surgical action triplet recognition
Context-aware decision support in the operating room can foster surgical...
research
∙
06/16/2020
Lung Segmentation and Nodule Detection in Computed Tomography Scan using a Convolutional Neural Network Trained Adversarially using Turing Test Loss
Lung cancer is the most common form of cancer found worldwide with a hig...
research
∙
04/28/2020
Identification of Cervical Pathology using Adversarial Neural Networks
Various screening and diagnostic methods have led to a large reduction o...
research
∙
04/26/2020
IROS 2019 Lifelong Robotic Vision Challenge – Lifelong Object Recognition Report
This report summarizes IROS 2019-Lifelong Robotic Vision Competition (Li...
research
∙
04/24/2020
A Two-Stage Multiple Instance Learning Framework for the Detection of Breast Cancer in Mammograms
Mammograms are commonly employed in the large scale screening of breast ...
research
∙
04/24/2020
Learning Decision Ensemble using a Graph Neural Network for Comorbidity Aware Chest Radiograph Screening
Chest radiographs are primarily employed for the screening of cardio, th...
research
∙
04/24/2020
A Systematic Search over Deep Convolutional Neural Network Architectures for Screening Chest Radiographs
Chest radiographs are primarily employed for the screening of pulmonary ...
research
∙
01/17/2020
CHAOS Challenge – Combined (CT-MR) Healthy Abdominal Organ Segmentation
Segmentation of abdominal organs has been a comprehensive, yet unresolve...
research
∙
08/03/2019
Adversarially Trained Convolutional Neural Networks for Semantic Segmentation of Ischaemic Stroke Lesion using Multisequence Magnetic Resonance Imaging
Ischaemic stroke is a medical condition caused by occlusion of blood sup...
research
∙
06/30/2019
Adversarially Trained Deep Neural Semantic Hashing Scheme for Subjective Search in Fashion Inventory
The simple approach of retrieving a closest match of a query image from ...
research
∙
06/10/2019
Unit Impulse Response as an Explainer of Redundancy in a Deep Convolutional Neural Network
Convolutional neural networks (CNN) are generally designed with a heuris...
research
∙
05/20/2019
Multitask Learning of Temporal Connectionism in Convolutional Networks using a Joint Distribution Loss Function to Simultaneously Identify Tools and Phase in Surgical Videos
Surgical workflow analysis is of importance for understanding onset and ...
research
∙
02/07/2019
Fully Convolutional Neural Network for Semantic Segmentation of Anatomical Structure and Pathologies in Colour Fundus Images Associated with Diabetic Retinopathy
Diabetic retinopathy (DR) is the most common form of diabetic eye diseas...
research
∙
01/21/2019
Segmentation of Lumen and External Elastic Laminae in Intravascular Ultrasound Images using Ultrasonic Backscattering Physics Initialized Multiscale Random Walks
Coronary artery disease accounts for a large number of deaths across the...
research
∙
01/21/2019
SUMNet: Fully Convolutional Model for Fast Segmentation of Anatomical Structures in Ultrasound Volumes
Ultrasound imaging is generally employed for real-time investigation of ...
research
∙
01/18/2019
Learning a Deep Convolution Network with Turing Test Adversaries for Microscopy Image Super Resolution
Adversarially trained deep neural networks have significantly improved p...
research
∙
01/17/2019
UltraCompression: Framework for High Density Compression of Ultrasound Volumes using Physics Modeling Deep Neural Networks
Ultrasound image compression by preserving speckle-based key information...
research
∙
05/17/2018
Fully Convolutional Model for Variable Bit Length and Lossy High Density Compression of Mammograms
Early works on medical image compression date to the 1980's with the imp...
research
∙
12/21/2017
Simulating Patho-realistic Ultrasound Images using Deep Generative Networks with Adversarial Learning
Ultrasound imaging makes use of backscattering of waves during their int...
research
∙
05/02/2017
Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data
Training deep fully convolutional neural networks (F-CNNs) for semantic ...
research
∙
04/07/2017
ReLayNet: Retinal Layer and Fluid Segmentation of Macular Optical Coherence Tomography using Fully Convolutional Network
Optical coherence tomography (OCT) is used for non-invasive diagnosis of...
research
∙
09/19/2016
Deep Neural Ensemble for Retinal Vessel Segmentation in Fundus Images towards Achieving Label-free Angiography
Automated segmentation of retinal blood vessels in label-free fundus ima...
research
∙
03/19/2016
DASA: Domain Adaptation in Stacked Autoencoders using Systematic Dropout
Domain adaptation deals with adapting behaviour of machine learning base...
research
∙
03/15/2016
