Jiapeng Luo

Orcid: 0000-0002-5585-8632

According to our database1, Jiapeng Luo authored at least 13 papers between 2016 and 2024.

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

2024
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites.
CoRR, 2024

Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
A Low-Latency Framework With Algorithm-Hardware Co-Optimization for 3-D Point Cloud.
IEEE Trans. Circuits Syst. II Express Briefs, November, 2023

A Unified Acceleration Solution Based on Deformable Network for Image Pixel Processing.
IEEE Trans. Circuits Syst. II Express Briefs, September, 2023

2022
A low latency traffic sign detection model with an automatic data labeling pipeline.
Neural Comput. Appl., 2022

Automatically search an optimal face detector for a specific deployment environment.
EURASIP J. Adv. Signal Process., 2022

An Efficient FPGA-based Accelerator for Deep Forest.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

2021
A Memory-Efficient Hardware Architecture for Deformable Convolutional Networks.
Proceedings of the IEEE Workshop on Signal Processing Systems, 2021

A Stage-wise Conversion Strategy for Low-Latency Deformable Spiking CNN.
Proceedings of the IEEE Workshop on Signal Processing Systems, 2021

2020
A lightweight face detector by integrating the convolutional neural network with the image pyramid.
Pattern Recognit. Lett., 2020

2018
WaspBase: a genomic resource for the interactions among parasitic wasps, insect hosts and plants.
Database J. Biol. Databases Curation, 2018

2017
ACE: an efficient and sensitive tool to detect insecticide resistance-associated mutations in insect acetylcholinesterase from RNA-Seq data.
BMC Bioinform., 2017

2016
A Non-linear Label Compression Coding Method Based on Five-Layer Auto-Encoder for Multi-label Classification.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016


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