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Found 12 papers, 4 papers with code
From Forks to Forceps: A New Framework for Instance Segmentation of Surgical Instruments
Minimally invasive surgeries and related applications demand surgical tool classification and segmentation at the instance level.
Measuring poverty in India with machine learning and remote sensing
In this paper, we use deep learning to estimate living conditions in India.
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
In this study, we explore and evaluate a score developed during the BraTS 2019 and BraTS 2020 task on uncertainty quantification (QU-BraTS) and designed to assess and rank uncertainty estimates for brain tumor multi-compartment segmentation.
Analysis of MRI Biomarkers for Brain Cancer Survival Prediction
In this scenario we analyse the potential of two novel neuroimaging feature families, extracted from brain parcellation atlases and spatial habitats, along with classical radiomic and geometric features; to study their combined predictive power for analysing overall survival.
REGroup: Rank-aggregating Ensemble of Generative Classifiers for Robust Predictions
Specifically, we devise an ensemble of these generative classifiers that rank-aggregates their predictions via a Borda count-based consensus.
CovidAID: COVID-19 Detection Using Chest X-Ray
This may be useful in an inpatient setting where the present systems are struggling to decide whether to keep the patient in the ward along with other patients or isolate them in COVID-19 areas.
Deep Radiomics for Brain Tumor Detection and Classification from Multi-Sequence MRI
LOPO testing, and testing on the holdout dataset are used to evaluate the performance of the ConvNets.
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i. e., 2012-2018.
A Joint 3D-2D based Method for Free Space Detection on Roads
Finally, we use the obtained road segmentation with the 3D depth data from monocular SLAM to detect the free space for the navigation purposes.
Robust Monocular SLAM for Egocentric Videos
The incremental nature of SOTA SLAM, in the presence of unreliable pose and 3D estimates in egocentric videos, with no opportunities for global loop closures, generates drifts and leads to the eventual failures of such techniques.
Computing Egomotion with Local Loop Closures for Egocentric Videos
Finding the camera pose is an important step in many egocentric video applications.
Fast Approximate Inference in Higher Order MRF-MAP Labeling Problems
Generic Cuts (GC) of Arora et al. [9] shows that when potentials are submodular, inference problems can be solved optimally in polynomial time for fixed size cliques.
