J
Jia-Hong Lee
Researcher at Academia Sinica
Publications - 16
Citations - 816
Jia-Hong Lee is an academic researcher from Academia Sinica. The author has contributed to research in topics: Deep learning & Artificial neural network. The author has an hindex of 6, co-authored 16 publications receiving 535 citations. Previous affiliations of Jia-Hong Lee include National Taiwan University of Science and Technology & National Taiwan University.
Papers
More filters
Journal ArticleDOI
ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI
Oskar Maier,Bjoern H. Menze,Janina von der Gablentz,Levin Häni,Mattias P. Heinrich,Matthias Liebrand,Stefan Winzeck,Abdul Basit,Paul Bentley,Liang Chen,Daan Christiaens,Francis Dutil,Karl Egger,Chaolu Feng,Ben Glocker,Michael Götz,Tom Haeck,Hanna-Leena Halme,Hanna-Leena Halme,Mohammad Havaei,Khan M. Iftekharuddin,Pierre-Marc Jodoin,Konstantinos Kamnitsas,Elias Kellner,Antti Korvenoja,Hugo Larochelle,Christian Ledig,Jia-Hong Lee,Frederik Maes,Qaiser Mahmood,Qaiser Mahmood,Klaus H. Maier-Hein,Richard McKinley,John Muschelli,Chris Pal,Linmin Pei,Janaki Raman Rangarajan,Syed M. S. Reza,David Robben,Daniel Rueckert,Eero Salli,Paul Suetens,Ching-Wei Wang,Matthias Wilms,Jan S. Kirschke,Ulrike M. Krämer,Thomas F. Münte,Peter Schramm,Roland Wiest,Heinz Handels,Mauricio Reyes +50 more
TL;DR: This paper proposes a common evaluation framework for automatic stroke lesion segmentation from MRIP, describes the publicly available datasets, and presents the results of the two sub‐challenges: Sub‐Acute Stroke Lesion Segmentation (SISS) and Stroke Perfusion Estimation (SPES).
Journal ArticleDOI
A benchmark for comparison of dental radiography analysis algorithms
Ching-Wei Wang,Cheng-Ta Huang,Jia-Hong Lee,Chung-Hsing Li,Sheng-Wei Chang,Ming-Jhih Siao,Tat-Ming Lai,Bulat Ibragimov,Tomaz Vrtovec,Olaf Ronneberger,Philipp Fischer,Timothy F. Cootes,Claudia Lindner +12 more
TL;DR: Based on the quantitative evaluation results, it is believed automatic dental radiography analysis is still a challenging and unsolved problem and the datasets and the evaluation software are made available to the research community, further encouraging future developments in this field.
Proceedings ArticleDOI
Increasingly Packing Multiple Facial-Informatics Modules in A Unified Deep-Learning Model via Lifelong Learning
TL;DR: The proposed packing-and-expanding method is effective and easy to implement, which can iteratively shrink and enlarge the model to integrate new functions and maintains the compactness in continual learning.
Proceedings ArticleDOI
Joint Estimation of Age and Gender from Unconstrained Face Images Using Lightweight Multi-Task CNN for Mobile Applications
TL;DR: Lightweight multi-task CNN as discussed by the authors uses depthwise separable convolution to reduce the model size and save the inference time for age and gender classification on the public challenging Adience dataset.
Proceedings ArticleDOI
Unifying and Merging Well-trained Deep Neural Networks for Inference Stage
Yi-Min Chou,Yi-Min Chou,Yi-Ming Chan,Yi-Ming Chan,Jia-Hong Lee,Jia-Hong Lee,Chih-Yi Chiu,Chu-Song Chen,Chu-Song Chen +8 more
TL;DR: The authors aligns the layers of the original networks and merges them into a unified model by sharing the representative codes of weights and further re-train the shared weights to fine-tune the performance of the merged model.