Gongbo Liang

According to our database, Gongbo Liang authored at least 36 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

H-Net: Heterogeneous Neural Network for Multi-Classification of Neuropsychiatric Disorders.

Liangliang Liu, Jinpu Xie, Jing Chang, Zhihong Liu, Tong Sun, Hongbo Qiao, Gongbo Liang, Wei Guo

IEEE J. Biomed. Health Informatics, September, 2024

Benchmark assessment for the DeepSpeed acceleration library on image classification.

Gongbo Liang, Mohammad Salem Atoum, Xin Xing, Izzat Alsmadi

Clust. Comput., June, 2024

Unveiling Roadway Hazards: Enhancing Fatal Crash Risk Estimation Through Multiscale Satellite Imagery and Self-Supervised Cross-Matching.

Gongbo Liang, Janet Zulu, Xin Xing, Nathan Jacobs

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

Using Large Language Models in Public Transit Systems, San Antonio as a case study.

Ramya Jonnala, Gongbo Liang, Jeong Yang, Izzat Alsmadi

CoRR, 2024

LEARNDB: A Comprehensive Toolkit for Database Education.

Guangming Xing, Tawfiq Salem, Gongbo Liang

Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024

Interactive Learning Modules for Fostering Secure Coding Proficiency in Introductory Programming Courses.

Guangming Xing, Gongbo Liang, Tawfiq Salem

Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024

Enhancing Machine Learning Based SQL Injection Detection Using Contextualized Word Embedding.

Janet Zulu, Bonian Han, Izzat Alsmadi, Gongbo Liang

Proceedings of the 2024 ACM Southeast Conference, 2024

2023

Simulated Quantum Mechanics-Based Joint Learning Network for Stroke Lesion Segmentation and TICI Grading.

Liangliang Liu, Jing Chang, Gongbo Liang, Shufeng Xiong

IEEE J. Biomed. Health Informatics, July, 2023

A spatiotemporal correlation deep learning network for brain penumbra disease.

Liangliang Liu, Pei Zhang, Gongbo Liang, Shufeng Xiong, Jianxin Wang, Guang Zheng

Neurocomputing, 2023

Mutation-Based Adversarial Attacks on Neural Text Detectors.

Gongbo Liang, Jesus Guerrero, Izzat Alsmadi

CoRR, 2023

2022

Contrastive Cross-Modal Pre-Training: A General Strategy for Small Sample Medical Imaging.

Gongbo Liang, Connor Greenwell, Yu Zhang, Xin Xing, Xiaoqin Wang, Ramakanth Kavuluru, Nathan Jacobs

IEEE J. Biomed. Health Informatics, 2022

LLRHNet: Multiple Lesions Segmentation Using Local-Long Range Features.

Liangliang Liu, Ying Wang, Jing Chang, Pei Zhang, Gongbo Liang, Hui Zhang

Frontiers Neuroinformatics, 2022

A Mutation-based Text Generation for Adversarial Machine Learning Applications.

Jesus Guerrero, Gongbo Liang, Izzat Alsmadi

CoRR, 2022

Benchmark Assessment for DeepSpeed Optimization Library.

Gongbo Liang, Izzat Alsmadi

CoRR, 2022

Development of CNN models for the enteral feeding tube positioning assessment on a small scale data set.

Gongbo Liang, Halemane Ganesh, Dylan Steffe, Liangliang Liu, Nathan Jacobs, Jie Zhang

BMC Medical Imaging, 2022

Advit: Vision Transformer On Multi-Modality Pet Images For Alzheimer Disease Diagnosis.

Xin Xing, Gongbo Liang, Yu Zhang, Subash Khanal, Ai-Ling Lin, Nathan Jacobs

Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Neural Network Decision-Making Criteria Consistency Analysis via Inputs Sensitivity.

Eric Xing, Liangliang Liu, Xin Xing, Yunni Qu, Nathan Jacobs, Gongbo Liang

Proceedings of the 26th International Conference on Pattern Recognition, 2022

Beware the Black-Box of Medical Image Generation: an Uncertainty Analysis by the Learned Feature Space.

Yunni Qu, David Yan, Eric Xing, Fengbo Zheng, Jie Zhang, Liangliang Liu, Gongbo Liang

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021

Multi-Modal Data Analysis for Alzheimer's Disease Diagnosis: An Ensemble Model Using Imagery and Genetic Features.

Qi Ying, Xin Xing, Liangliang Liu, Ai-Ling Lin, Nathan Jacobs, Gongbo Liang

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Alzheimer's Disease Classification Using 2D Convolutional Neural Networks.

Gongbo Liang, Xin Xing, Liangliang Liu, Yu Zhang, Qi Ying, Ai-Ling Lin, Nathan Jacobs

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Dynamic Feature Alignment for Semi-supervised Domain Adaptation.

Yu Zhang, Gongbo Liang, Nathan Jacobs

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

Optical Wavelength Guided Self-Supervised Feature Learning For Galaxy Cluster Richness Estimate.

Gongbo Liang, Yuanyuan Su, Sheng-Chieh Lin, Yu Zhang, Yuanyuan Zhang, Nathan Jacobs

CoRR, 2020

Weakly-Supervised Feature Learning via Text and Image Matching.

Gongbo Liang, Connor Greenwell, Yu Zhang, Xiaoqin Wang, Ramakanth Kavuluru, Nathan Jacobs

CoRR, 2020

Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification.

Gongbo Liang, Yu Zhang, Xiaoqin Wang, Nathan Jacobs

CoRR, 2020

Unsupervised Domain Adaptation for Mammogram Image Classification: A Promising Tool for Model Generalization.

Yu Zhang, Gongbo Liang, Nathan Jacobs, Xiaoqin Wang

CoRR, 2020

Multi-Branch Attention Networks for Classifying Galaxy Clusters.

Yu Zhang, Gongbo Liang, Yuanyuan Su, Nathan Jacobs

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Weakly-Supervised Self-Training for Breast Cancer Localization^*.

Gongbo Liang, Xiaoqin Wang, Yu Zhang, Nathan Jacobs

Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Dynamic Image for 3D MRI Image Alzheimer's Disease Classification.

Xin Xing, Gongbo Liang, Hunter Blanton, Muhammad Usman Rafique, Chris Wang, Ai-Ling Lin, Nathan Jacobs

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

Improved Trainable Calibration Method for Neural Networks.

Gongbo Liang, Yu Zhang, Xiaoqin Wang, Nathan Jacobs

Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019

GANai: Standardizing CT Images using Generative Adversarial Network with Alternative Improvement.

Gongbo Liang, Sajjad Fouladvand, Jie Zhang, Michael A. Brooks, Nathan Jacobs, Jin Chen

Proceedings of the 2019 IEEE International Conference on Healthcare Informatics, 2019

Defense-PointNet: Protecting PointNet Against Adversarial Attacks.

Yu Zhang, Gongbo Liang, Tawfiq Salem, Nathan Jacobs

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2D Convolutional Neural Networks for 3D Digital Breast Tomosynthesis Classification.

Yu Zhang, Xiaoqin Wang, Hunter Blanton, Gongbo Liang, Xin Xing, Nathan Jacobs

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Joint 2D-3D Breast Cancer Classification.

Gongbo Liang, Xiaoqin Wang, Yu Zhang, Xin Xing, Hunter Blanton, Tawfiq Salem, Nathan Jacobs

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018

Enhancing Radiomic Features of CT Images using Generative Adversarial Network with Alternative Improvement.

Gongbo Liang, Jie Zhang, Michael A. Brooks, Jessica Howard, Jin Chen

Proceedings of the AMIA 2018, 2018

2016

Pedestrian detection via a leg-driven physiology framework.

Gongbo Liang, Qi Li, Xiangui Kang

Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

2015

A geometric framework for stop sign detection.

Qi Li, Gongbo Liang, Yongyi Gong

Proceedings of the IEEE China Summit and International Conference on Signal and Information Processing, 2015