Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

A 65-nm CMOS Lossless Bio-Signal Compression Circuit With 250 FemtoJoule Performance Per Bit.

C. Crispin-Bailey, C. Dai, and J. Austin. IEEE Trans. Biomed. Circuits Syst., 13 (5): 1087-1100 (2019)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Chengliang Li

Other publications of authors with the same name

A lossless data reduction technique for wireless EEG recorders and its use in selective data filtering for seizure monitoring.C. Dai, and C. Bailey. EMBC, page 6186-6189. IEEE, (2015)Transfer Learning from Partial Annotations for Whole Brain Segmentation.C. Dai, Y. Mo, E. Angelini, Y. Guo, and W. Bai. DART/MIL3ID@MICCAI, volume 11795 of Lecture Notes in Computer Science, page 199-206. Springer, (2019)Deep Generative Model-Based Quality Control for Cardiac MRI Segmentation.S. Wang, G. Tarroni, C. Qin, Y. Mo, C. Dai, C. Chen, B. Glocker, Y. Guo, D. Rueckert, and W. Bai. MICCAI (4), volume 12264 of Lecture Notes in Computer Science, page 88-97. Springer, (2020)A 65-nm CMOS Lossless Bio-Signal Compression Circuit With 250 FemtoJoule Performance Per Bit.C. Crispin-Bailey, C. Dai, and J. Austin. IEEE Trans. Biomed. Circuits Syst., 13 (5): 1087-1100 (2019)Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records.J. Zhang, X. Zhang, K. Sun, X. Yang, C. Dai, and Y. Guo. BIBM, page 598-603. IEEE, (2019)Efficient Deep Representation Learning by Adaptive Latent Space Sampling.Y. Mo, S. Wang, C. Dai, R. Zhou, Z. Teng, W. Bai, and Y. Guo. CoRR, (2020)Suggestive Annotation of Brain Tumour Images with Gradient-Guided Sampling.C. Dai, S. Wang, Y. Mo, K. Zhou, E. Angelini, Y. Guo, and W. Bai. MICCAI (4), volume 12264 of Lecture Notes in Computer Science, page 156-165. Springer, (2020)Self-training for Brain Tumour Segmentation with Uncertainty Estimation and Biophysics-Guided Survival Prediction.C. Dai, S. Wang, H. Raynaud, Y. Mo, E. Angelini, Y. Guo, and W. Bai. BrainLes@MICCAI (1), volume 12658 of Lecture Notes in Computer Science, page 514-523. Springer, (2020)Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification.X. Zhang, J. Zhang, K. Sun, X. Yang, C. Dai, and Y. Guo. BIBM, page 765-769. IEEE, (2019)Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction.S. Wang, C. Dai, Y. Mo, E. Angelini, Y. Guo, and W. Bai. BrainLes@MICCAI (2), volume 11993 of Lecture Notes in Computer Science, page 61-72. Springer, (2019)

BibSonomy

Disambiguation of "Dai, Chengliang"

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

A 65-nm CMOS Lossless Bio-Signal Compression Circuit With 250 FemtoJoule Performance Per Bit.

Please choose a person to relate this publication to

Chengliang Li

Chengliang Li

Chengliang Li

Chengliang Li

Chengliang Li

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Dai, Chengliang"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A 65-nm CMOS Lossless Bio-Signal Compression Circuit With 250 FemtoJoule Performance Per Bit.

Please choose a person to relate this publication to

Chengliang Li

Chengliang Li

Chengliang Li

Chengliang Li

Chengliang Li

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

A 65-nm CMOS Lossless Bio-Signal Compression Circuit With 250 FemtoJoule Performance Per Bit.