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Found 8 papers, 1 papers with code
How important are faces for person re-identification?
This paper investigates the dependence of existing state-of-the-art person re-identification models on the presence and visibility of human faces.
Investigating Class-level Difficulty Factors in Multi-label Classification Problems
This work investigates the use of class-level difficulty factors in multi-label classification problems for the first time.
Predicting knee osteoarthritis severity: comparative modeling based on patient's data and plain X-ray images
Knee osteoarthritis (KOA) is a disease that impairs knee function and causes pain.
Assessing Knee OA Severity with CNN attention-based end-to-end architectures
This work proposes a novel end-to-end convolutional neural network (CNN) architecture to automatically quantify the severity of knee osteoarthritis (OA) using X-Ray images, which incorporates trainable attention modules acting as unsupervised fine-grained detectors of the region of interest (ROI).
Feature Learning to Automatically Assess Radiographic Knee Osteoarthritis Severity
Also, this chapter demonstrates that feature learning in a supervised manner is more effective than using conventional handcrafted features for automatic detection of knee joints and fine-grained knee OA image classification.
Automatic Detection of Knee Joints and Quantification of Knee Osteoarthritis Severity using Convolutional Neural Networks
We introduce a new approach to automatically detect the knee joints using a fully convolutional neural network (FCN).
An Interactive Segmentation Tool for Quantifying Fat in Lumbar Muscles using Axial Lumbar-Spine MRI
In this paper, we propose a method to precisely quantify the fat deposition / infiltration in a user-defined region of the lumbar muscles, which may aid better diagnosis and analysis.
Quantifying Radiographic Knee Osteoarthritis Severity using Deep Convolutional Neural Networks
We demonstrate that classification accuracy can be significantly improved using deep convolutional neural network models pre-trained on ImageNet and fine-tuned on knee OA images.
