Yong Xia focuses on Artificial intelligence, Pattern recognition, Segmentation, Image segmentation and Deep learning. His Artificial intelligence study frequently links to adjacent areas such as Machine learning. His Pattern recognition research is multidisciplinary, incorporating elements of Contextual image classification, Feature, Computer vision and Image processing.
Much of his study explores Segmentation relationship to Tumor progression. His Image segmentation research focuses on Cluster analysis and how it connects with Fuzzy logic, Weighting, Rough set and Euclidean distance. His Deep learning study integrates concerns from other disciplines, such as Feature extraction and Nodule.
His primary scientific interests are in Artificial intelligence, Pattern recognition, Segmentation, Image segmentation and Deep learning. The study incorporates disciplines such as Machine learning and Computer vision in addition to Artificial intelligence. His Pattern recognition study also includes fields such as
His Segmentation research includes elements of Brain atlas, Voxel and Medical imaging. His Image segmentation research incorporates elements of PET-CT and Fuzzy clustering. His studies in Deep learning integrate themes in fields like Lung cancer and Nodule.
His primary areas of investigation include Artificial intelligence, Pattern recognition, Segmentation, Deep learning and Image segmentation. Artificial intelligence is frequently linked to Machine learning in his study. His work on Anomaly detection as part of general Pattern recognition study is frequently connected to Process, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
Many of his research projects under Segmentation are closely connected to Encoder with Encoder, tying the diverse disciplines of science together. His research in Deep learning intersects with topics in Pyramid, Feature extraction, Relation and Feature vector. His biological study spans a wide range of topics, including Residual, Pyramid and Benchmark.
Yong Xia mainly investigates Artificial intelligence, Pattern recognition, Deep learning, Segmentation and Convolutional neural network. His works in Feature, Image segmentation, Anomaly detection, Feature extraction and Binary classification are all subjects of inquiry into Artificial intelligence. Yong Xia interconnects Retina, Retinal vessel and Fundus in the investigation of issues within Feature.
His Feature extraction research incorporates themes from Contextual image classification, MNIST database, Normalization and Crossover. His studies deal with areas such as Lesion, Skin cancer, Minimum bounding box, Lymph node and Reinforcement learning as well as Segmentation. His study in Convolutional neural network is interdisciplinary in nature, drawing from both Artificial neural network, Supervised learning, Pixel and Chest radiograph.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer.
arXiv: Computer Vision and Pattern Recognition (2018)
COVID-19 Screening on Chest X-ray Images Using Deep Learning based Anomaly Detection
Jianpeng Zhang;Yutong Xie;Yi Li;Chunhua Shen.
Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT
Yutong Xie;Yong Xia;Jianpeng Zhang;Yang Song.
IEEE Transactions on Medical Imaging (2019)
Attention Residual Learning for Skin Lesion Classification
Jianpeng Zhang;Yutong Xie;Yong Xia;Chunhua Shen.
IEEE Transactions on Medical Imaging (2019)
Robust saliency detection via regularized random walks ranking
Changyang Li;Yuchen Yuan;Weidong Cai;Yong Xia.
computer vision and pattern recognition (2015)
Medical image classification using synergic deep learning.
Jianpeng Zhang;Yutong Xie;Qi Wu;Yong Xia.
Medical Image Analysis (2019)
Fusing texture, shape and deep model-learned information at decision level for automated classification of lung nodules on chest CT
Yutong Xie;Jianpeng Zhang;Yong Xia;Michael J. Fulham.
Information Fusion (2018)
Morphology-based multifractal estimation for texture segmentation
Yong Xia;Dagan Feng;Rongchun Zhao.
IEEE Transactions on Image Processing (2006)
GA-SVM based feature selection and parameter optimization in hospitalization expense modeling
Zhou Tao;Lu Huiling;Wang Wenwen;Yong Xia.
Applied Soft Computing (2019)
Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly Detection
Jianpeng Zhang;Yutong Xie;Guansong Pang;Zhibin Liao.
arXiv: Image and Video Processing (2020)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: