Rongjian Li

According to our database¹, Rongjian Li authored at least 18 papers between 2013 and 2024.

Collaborative distances:

Dijkstra number² of three.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

Research on Disruptive Technology Prediction Methods Based on BERT Model and Graph Theory Analysis.

[BibT_eX]

[DOI]

Proceedings of the World Conference of AI-Powered Innovation and Inventive Design, 2024

Research on Method of Flexible Mold Surface Formation Based on Point Cloud and Neural Network.

[BibT_eX]

[DOI]

Proceedings of the World Conference of AI-Powered Innovation and Inventive Design, 2024

2020

Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis.

[BibT_eX]

[DOI]

IEEE Trans. Big Data, 2020

The Research on the Strategy of College English Teaching Mode Based on Mobile Terminal Under the Background of Internet+.

[BibT_eX]

[DOI]

Rongjian Li

Proceedings of the 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, 2020

2018

Exploratory Studies Detecting Secondary Structures in Medium Resolution 3D Cryo-EM Images Using Deep Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 2018 ACM International Conference on Bioinformatics, 2018

2017

Deep Learning Segmentation of Optical Microscopy Images Improves 3-D Neuron Reconstruction.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2017

2016

Machine Learning Methods for Medical and Biological Image Computing.

[BibT_eX]

[DOI]

Rongjian Li

PhD thesis, 2016

Deep convolutional neural networks for detecting secondary structures in protein density maps from cryo-electron microscopy.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

2015

Sparsity Learning Formulations for Mining Time-Varying Data.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2015

Deep convolutional neural networks for multi-modality isointense infant brain image segmentation.

[BibT_eX]

[DOI]

NeuroImage, 2015

Evolutionary soft co-clustering: formulations, algorithms, and applications.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2015

Deep convolutional neural networks for annotating gene expression patterns in the mouse brain.

[BibT_eX]

[DOI]

BMC Bioinform., 2015

2014

Sparse K-Means with ℓ<sub>∞</sub>/ℓ<sub>0</sub> Penalty for High-Dimensional Data Clustering.

[BibT_eX]

[DOI]

CoRR, 2014

Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns.

[BibT_eX]

[DOI]

Rongjian Li

Wenlu Zhang

Shuiwang Ji

BMC Bioinform., 2014

Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

2013

A Probabilistic Latent Semantic Analysis Model for Coclustering the Mouse Brain Atlas.

[BibT_eX]

[DOI]

Shuiwang Ji

Wenlu Zhang

Rongjian Li

IEEE ACM Trans. Comput. Biol. Bioinform., 2013

A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis.

[BibT_eX]

[DOI]

BMC Bioinform., 2013

Sparse K-Means with the l_q(0leq q< 1) Constraint for High-Dimensional Data Clustering.

[BibT_eX]

[DOI]

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Rongjian Li

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