Yunqiang Li

Orcid: 0009-0005-3881-8937

According to our database1, Yunqiang Li authored at least 14 papers between 2017 and 2024.

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

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
RGBTSDF: An Efficient and Simple Method for Color Truncated Signed Distance Field (TSDF) Volume Fusion Based on RGB-D Images.
Remote. Sens., September, 2024

Binary Deep Learning: Binary Weights and Semantic Binary Data Compression.
PhD thesis, 2024

2023
Understanding weight-magnitude hyperparameters in training binary networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Differentiable Transportation Pruning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Equal Bits: Enforcing Equally Distributed Binary Network Weights.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
3D geological structure inversion from Noddy-generated magnetic data using deep learning methods.
Comput. Geosci., 2021

MZ Fiber Optic Temperature Sensor Based on Staggered Fusion Double Cone Type.
Proceedings of the 13th International Conference on Advanced Infocomm Technology, 2021

Deep Unsupervised Image Hashing by Maximizing Bit Entropy.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Deep Position-Sensitive Tracking.
IEEE Trans. Multim., 2020

WeightAlign: Normalizing Activations by Weight Alignment.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Zoom-CAM: Generating Fine-grained Pixel Annotations from Image Labels.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019
Push for Quantization: Deep Fisher Hashing.
Proceedings of the 30th British Machine Vision Conference 2019, 2019

2017
An Ensemble Hashing Framework for Fast Image Retrieval.
Proceedings of the Advances in Internetworking, 2017

Image Retrieval via Balanced and Maximum Variance Deep Hashing.
Proceedings of the Computer Vision - Second CCF Chinese Conference, 2017


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