Jinglan Liu

Orcid: 0000-0002-5699-0870

According to our database1, Jinglan Liu authored at least 21 papers between 2014 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2021
Multi-Cycle-Consistent Adversarial Networks for Edge Denoising of Computed Tomography Images.
ACM J. Emerg. Technol. Comput. Syst., 2021

The New Exploration of German Teaching based on Multimedia Technology.
Proceedings of the ICISCAE 2021: 4th International Conference on Information Systems and Computer Aided Education, Dalian, China, September 24, 2021

2020
Binarizing Weights Wisely for Edge Intelligence: Guide for Partial Binarization of Deconvolution-Based Generators.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020

Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Multi-Cycle-Consistent Adversarial Networks for CT Image Denoising.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Revisiting the Evaluation of Uncertainty Estimation and Its Application to Explore Model Complexity-Uncertainty Trade-Off.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Evaluation of Neural Network Uncertainty Estimation with Application to Resource-Constrained Platforms.
CoRR, 2019

On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Design-Phase Buffer Allocation for Post-Silicon Clock Binning by Iterative Learning.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2018

Efficient Hardware Implementation of Cellular Neural Networks with Incremental Quantization and Early Exit.
ACM J. Emerg. Technol. Comput. Syst., 2018

PBGAN: Partial Binarization of Deconvolution Based Generators.
CoRR, 2018

On the Universal Approximability of Quantized ReLU Neural Networks.
CoRR, 2018

Optimizing Boiler Control in Real-Time with Machine Learning for Sustainability.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017
Generative adversarial network based scalable on-chip noise sensor placement.
Proceedings of the 30th IEEE International System-on-Chip Conference, 2017

Efficient hardware implementation of cellular neural networks with powers-of-two based incremental quantization.
Proceedings of the Neuromorphic Computing Symposium, 2017

Edge segmentation: Empowering mobile telemedicine with compressed cellular neural networks.
Proceedings of the 2017 IEEE/ACM International Conference on Computer-Aided Design, 2017

2016
Selective body biasing for post-silicon tuning of sub-threshold designs: A semi-infinite programming approach with Incremental Hypercubic Sampling.
Integr., 2016

Privacy protection via appliance scheduling in smart homes.
Proceedings of the 35th International Conference on Computer-Aided Design, 2016

2015
1-Bit Compressed Sensing Based Framework for Built-in Resonance Frequency Prediction Using On-Chip Noise Sensors.
Proceedings of the IEEE/ACM International Conference on Computer-Aided Design, 2015

Effective CAD Research in the Sea of Papers.
Proceedings of the IEEE/ACM International Conference on Computer-Aided Design, 2015

2014
HW/SW partitioning for region-based dynamic partial reconfigurable FPGAs.
Proceedings of the 32nd IEEE International Conference on Computer Design, 2014


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