Juan Wang

发表

An image-retrieval aided diagnosis system for clustered microcalcifications

Robert M. Nishikawa, Yongyi Yang, Miles N. Wernick, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

CDRNet: accurate cup-to-disc ratio measurement with tight bounding box supervision in fundus photography using deep learning

Juan Wang, Bin Xia, 2021, Multimedia Tools and Applications.

Attention-Aware Learning for Hyperparameter Prediction in Image Processing Pipelines

Juan Wang, Bing Li, Congxuan Zhang, 2022, ECCV.

Detecting Cardiovascular Disease from Mammograms With Deep Learning

Sabee Molloi, Juan Wang, Pierre Baldi, 2017, IEEE Transactions on Medical Imaging.

A context-sensitive deep learning approach for microcalcification detection in mammograms

Yongyi Yang, Juan Wang, Yongyi Yang, 2018, Pattern Recognit..

Accurate Cup-to-Disc Ratio Measurement with Tight Bounding Box Supervision in Fundus Photography pdf

Juan Wang, Bin Xia, Juan Wang, 2021, ArXiv.

Deep Learning Features for Modeling Perceptual Similarity in Microcalcification Lesion Retrieval

Yongyi Yang, Liang Lei, Juan Wang, 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

A Hierarchical Learning Approach for Detection of Clustered Microcalcifications in Mammograms

Yongyi Yang, Juan Wang, Yongyi Yang, 2019, 2019 IEEE International Conference on Image Processing (ICIP).

Quantitative study of image features of clustered microcalcifications in for-presentation mammograms

Robert M. Nishikawa, Yongyi Yang, Juan Wang, 2016, 2016 IEEE International Conference on Image Processing (ICIP).

Boosted classification of breast cancer by retrieval of cases having similar disease likelihood

Yongyi Yang, Juan Wang, Yongyi Yang, 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Feature saliency analysis for perceptual similarity of clustered microcalcifications

Yongyi Yang, Juan Wang, Yongyi Yang, 2015, 2015 IEEE International Conference on Image Processing (ICIP).

Spatial density modeling for discirminating between benign and malignant microcalcification lesions

Yongyi Yang, Juan Wang, Yongyi Yang, 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.

Improving SVM classifier with prior knowledge in microcalcification detection1

Yongyi Yang, Yan Yang, Juan Wang, 2012, 2012 19th IEEE International Conference on Image Processing.

Exploiting rotation invariance with SVM classifier for microcalcification detection

Yongyi Yang, Yan Yang, Juan Wang, 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

Classification of Malignant and Benign Tumors

Yongyi Yang, Juan Wang, Issam El Naqa, 2022, Machine and Deep Learning in Oncology, Medical Physics and Radiology.

Global detection approach for clustered microcalcifications in mammograms using a deep learning network

Yongyi Yang, Juan Wang, Robert M Nishikawa, 2017, Journal of medical imaging.

Voiceprint recognition of Parkinson patients based on deep learning pdf

Xiangjian He, Ying Zhang, Juan Wang, 2018, ArXiv.

Parkinson’s Disease Detection Based on Spectrogram-Deep Convolutional Generative Adversarial Network Sample Augmentation

Zhi-Jing Xu, Rong-Fei Wang, Juan Wang, 2020, IEEE Access.

Reduction of false positive detection in clustered microcalcifications

Robert M. Nishikawa, Yongyi Yang, Juan Wang, 2013, 2013 IEEE International Conference on Image Processing.

Quantitative comparison of clustered microcalcifications in for‐presentation and for‐processing mammograms in full‐field digital mammography

Yongyi Yang, Juan Wang, Robert M Nishikawa, 2017, Medical physics.

Analysis of perceived similarity between pairs of microcalcification clusters in mammograms.

Yongyi Yang, Hao Jing, Miles N Wernick, 2014, Medical physics.

Exploring perceptually similar cases with multi-dimensional scaling

Robert M. Nishikawa, Yongyi Yang, Miles N. Wernick, 2014, Medical Imaging.

Bone Age Assessment Based on Deep Convolutional Features and Fast Extreme Learning Machine Algorithm

Juan Wang, Jiaqi Teng, Yukun Chen, 2022, Frontiers in Energy Research.

Bounding Box Tightness Prior for Weakly Supervised Image Segmentation pdf

Juan Wang, Bin Xia, Juan Wang, 2021, MICCAI.

Improving the accuracy in detection of clustered microcalcifications with a context-sensitive classification model.

R. Nishikawa, Yongyi Yang, Juan Wang, 2015, Medical physics.

Adaboost with dummy-variable modeling for reduction of false positives in detection of clustered microcalcifications

Yongyi Yang, Juan Wang, Yongyi Yang, 2014, 2014 IEEE International Conference on Image Processing (ICIP).

Weakly Supervised Image Segmentation Beyond Tight Bounding Box Annotations

Juan Wang, Bin Xia, 2023, Comput. Biol. Medicine.

Polar Transformation Based Multiple Instance Learning Assisting Weakly Supervised Image Segmentation With Loose Bounding Box Annotations

Juan Wang, Bin Xia, 2022, ArXiv.