Gongbo Liang - RankMe

56 papers A* 1A 2B 4Misc 1Journal 29Unranked 19

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Beta Distribution Learning for Reliable Roadway Crash Risk Assessment. AAAI Ahmad Elallaf, Nathan Jacobs, Xinyue Ye, Mei Chen, Gongbo Liang
2026	—	`conf`	ChartCode: A Flowchart-Centric Educational Tool for Introductory Programming. SIGCSE (1) Guangming Xing, Gongbo Liang, Tawfiq Salem
2026	J	`jnl`	MedProbCLIP: Probabilistic Adaptation of Vision-Language Foundation Model for Reliable Radiograph-Report Retrieval. CoRR Ahmad Elallaf, Yu Zhang, Yuktha Priya Masupalli, Jeong Yang, Young Lee, Zechun Cao, Gongbo Liang
2025	J	`jnl`	Benchmarking Robustness of Contrastive Learning Models for Medical Image-Report Retrieval. CoRR Demetrio Deanda, Yuktha Priya Masupalli, Jeong Yang, Young Lee, Zechun Cao, Gongbo Liang
2025	J	`jnl`	Beta Distribution Learning for Reliable Roadway Crash Risk Assessment. CoRR Ahmad Elallaf, Nathan Jacobs, Xinyue Ye, Mei Chen, Gongbo Liang
2025	J	`jnl`	Can Contrastive Learning Improve Class-Imbalanced Diffusion Model? CoRR Fang Chen, Alex Villa, Gongbo Liang, Xiaoyi Lu, Meng Tang
2025	—	`conf`	ChartCode: A Flowchart-Based Tool for Introductory Programming Courses. SIGCSE (2) Guangming Xing, Tawfiq Salem, Gongbo Liang
2025	J	`jnl`	Defending mutation-based adversarial text perturbation: a black-box approach. Clust. Comput. Demetrio Deanda, Izzat Alsmadi, Jesús Guerrero, Gongbo Liang
2025	J	`jnl`	Exploring the Potential of Large Language Models in Public Transportation: San Antonio Case Study. CoRR Ramya Jonnala, Gongbo Liang, Jeong Yang, Izzat Alsmadi
2025	J	`jnl`	Machine Learning-Based Vulnerability Detection in Rust Code Using LLVM IR and Transformer Model. Mach. Learn. Knowl. Extr. Young Lee, Syeda Jannatul Boshra, Jeong Yang, Zechun Cao, Gongbo Liang
2025	J	`jnl`	Measuring and Improving the Efficiency of Python Code Generated by LLMs Using CoT Prompting and Fine-Tuning. IEEE Access Ramya Jonnala, Jeong Yang, Young Lee, Gongbo Liang, Zechun Cao
2025	—	`conf`	PortrAid: An AI-Driven Portrait Assistant for Professional-Quality Image Composition. ACM Southeast Regional Conference Jaspal Singh Kahlon, Gongbo Liang
2024	—	`conf`	Analyzing the Usability, Performance, and Cost-Efficiency of Deploying ML Models on BigQuery ML and Vertex AI in Google Cloud. ICCBDC Hongyu Wang, Jeong Yang, Gongbo Liang, Young Lee, Zechun Cao
2024	J	`jnl`	Benchmark assessment for the DeepSpeed acceleration library on image classification. Clust. Comput. Gongbo Liang, Mohammed Salem Atoum, Xin Xing, Izzat Alsmadi
2024	—	`conf`	Enhancing Machine Learning Based SQL Injection Detection Using Contextualized Word Embedding. ACM Southeast Regional Conference Janet Zulu, Bonian Han, Izzat Alsmadi, Gongbo Liang
2024	J	`jnl`	H-Net: Heterogeneous Neural Network for Multi-Classification of Neuropsychiatric Disorders. IEEE J. Biomed. Health Informatics Liangliang Liu, Jinpu Xie, Jing Chang, Zhihong Liu, Tong Sun, Hongbo Qiao, Gongbo Liang, Wei Guo
2024	B	`conf`	Improving Medical Imaging Model Calibration through Probabilistic Embedding. IEEE Big Data Bonian Han, Yuktha Priya Masupalli, Xin Xing, Gongbo Liang
2024	—	`conf`	Interactive Learning Modules for Fostering Secure Coding Proficiency in Introductory Programming Courses. SIGCSE (2) Guangming Xing, Gongbo Liang, Tawfiq Salem
2024	—	`conf`	LEARNDB: A Comprehensive Toolkit for Database Education. SIGCSE (2) Guangming Xing, Tawfiq Salem, Gongbo Liang
2024	—	`conf`	Multi-Scale Self-Supervised Consistency Training for Trustworthy Medical Imaging Classification. EMBC Bonian Han, Cristian Moran, Jeong Yang, Young Lee, Zechun Cao, Gongbo Liang
2024	J	`jnl`	Unveiling Roadway Hazards: Enhancing Fatal Crash Risk Estimation Through Multiscale Satellite Imagery and Self-Supervised Cross-Matching. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Gongbo Liang, Janet Zulu, Xin Xing, Nathan Jacobs
2024	J	`jnl`	Using Large Language Models in Public Transit Systems, San Antonio as a case study. CoRR Ramya Jonnala, Gongbo Liang, Jeong Yang, Izzat Alsmadi
2023	J	`jnl`	A spatiotemporal correlation deep learning network for brain penumbra disease. Neurocomputing Liangliang Liu, Pei Zhang, Gongbo Liang, Shufeng Xiong, Jianxin Wang, Guang Zheng
2023	J	`jnl`	Mutation-Based Adversarial Attacks on Neural Text Detectors. CoRR Gongbo Liang, Jesús Guerrero, Izzat Alsmadi
2023	J	`jnl`	Simulated Quantum Mechanics-Based Joint Learning Network for Stroke Lesion Segmentation and TICI Grading. IEEE J. Biomed. Health Informatics Liangliang Liu, Jing Chang, Gongbo Liang, Shufeng Xiong
2022	J	`jnl`	A Mutation-based Text Generation for Adversarial Machine Learning Applications. CoRR Jesús Guerrero, Gongbo Liang, Izzat Alsmadi
2022	—	`conf`	Advit: Vision Transformer On Multi-Modality Pet Images For Alzheimer Disease Diagnosis. ISBI Xin Xing, Gongbo Liang, Yu Zhang, Subash Khanal, Ai-Ling Lin, Nathan Jacobs
2022	J	`jnl`	Benchmark Assessment for DeepSpeed Optimization Library. CoRR Gongbo Liang, Izzat Alsmadi
2022	—	`conf`	Beware the Black-Box of Medical Image Generation: an Uncertainty Analysis by the Learned Feature Space. EMBC Yunni Qu, David Yan, Eric Xing, Fengbo Zheng, Jie Zhang, Liangliang Liu, Gongbo Liang
2022	J	`jnl`	Contrastive Cross-Modal Pre-Training: A General Strategy for Small Sample Medical Imaging. IEEE J. Biomed. Health Informatics Gongbo Liang, Connor Greenwell, Yu Zhang, Xin Xing, Xiaoqin Wang, Ramakanth Kavuluru, Nathan Jacobs
2022	J	`jnl`	Development of CNN models for the enteral feeding tube positioning assessment on a small scale data set. BMC Medical Imaging Gongbo Liang, Halemane Ganesh, Dylan Steffe, Liangliang Liu, Nathan Jacobs, Jie Zhang
2022	J	`jnl`	LLRHNet: Multiple Lesions Segmentation Using Local-Long Range Features. Frontiers Neuroinformatics Liangliang Liu, Ying Wang, Jing Chang, Pei Zhang, Gongbo Liang, Hui Zhang
2022	B	`conf`	Neural Network Decision-Making Criteria Consistency Analysis via Inputs Sensitivity. ICPR Eric Xing, Liangliang Liu, Xin Xing, Yunni Qu, Nathan Jacobs, Gongbo Liang
2021	—	`conf`	Alzheimer's Disease Classification Using 2D Convolutional Neural Networks. EMBC Gongbo Liang, Xin Xing, Liangliang Liu, Yu Zhang, Qi Ying, Ai-Ling Lin, Nathan Jacobs
2021	A	`conf`	Dynamic Feature Alignment for Semi-supervised Domain Adaptation. BMVC Yu Zhang, Gongbo Liang, Nathan Jacobs
2021	J	`jnl`	Dynamic Feature Alignment for Semi-supervised Domain Adaptation. CoRR Yu Zhang, Gongbo Liang, Nathan Jacobs
2021	—	`conf`	Multi-Modal Data Analysis for Alzheimer's Disease Diagnosis: An Ensemble Model Using Imagery and Genetic Features. EMBC Qi Ying, Xin Xing, Liangliang Liu, Ai-Ling Lin, Nathan Jacobs, Gongbo Liang
2020	J	`jnl`	2D Convolutional Neural Networks for 3D Digital Breast Tomosynthesis Classification. CoRR Yu Zhang, Xiaoqin Wang, Hunter Blanton, Gongbo Liang, Xin Xing, Nathan Jacobs
2020	J	`jnl`	Defense-PointNet: Protecting PointNet Against Adversarial Attacks. CoRR Yu Zhang, Gongbo Liang, Tawfiq Salem, Nathan Jacobs
2020	—	`conf`	Dynamic Image for 3D MRI Image Alzheimer's Disease Classification. ECCV Workshops (1) Xin Xing, Gongbo Liang, Hunter Blanton, Muhammad Usman Rafique, Chris Wang, Ai-Ling Lin, Nathan Jacobs
2020	J	`jnl`	Dynamic Image for 3D MRI Image Alzheimer's Disease Classification. CoRR Xin Xing, Gongbo Liang, Hunter Blanton, Muhammad Usman Rafique, Chris Wang, Ai-Ling Lin, Nathan Jacobs
2020	J	`jnl`	Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification. CoRR Gongbo Liang, Yu Zhang, Xiaoqin Wang, Nathan Jacobs
2020	A	`conf`	Improved Trainable Calibration Method for Neural Networks. BMVC Gongbo Liang, Yu Zhang, Xiaoqin Wang, Nathan Jacobs
2020	J	`jnl`	Joint 2D-3D Breast Cancer Classification. CoRR Gongbo Liang, Xiaoqin Wang, Yu Zhang, Xin Xing, Hunter Blanton, Tawfiq Salem, Nathan Jacobs
2020	B	`conf`	Multi-Branch Attention Networks for Classifying Galaxy Clusters. ICPR Yu Zhang, Gongbo Liang, Yuanyuan Su, Nathan Jacobs
2020	J	`jnl`	Optical Wavelength Guided Self-Supervised Feature Learning For Galaxy Cluster Richness Estimate. CoRR Gongbo Liang, Yuanyuan Su, Sheng-Chieh Lin, Yu Zhang, Yuanyuan Zhang, Nathan Jacobs
2020	J	`jnl`	Unsupervised Domain Adaptation for Mammogram Image Classification: A Promising Tool for Model Generalization. CoRR Yu Zhang, Gongbo Liang, Nathan Jacobs, Xiaoqin Wang
2020	J	`jnl`	Weakly-Supervised Feature Learning via Text and Image Matching. CoRR Gongbo Liang, Connor Greenwell, Yu Zhang, Xiaoqin Wang, Ramakanth Kavuluru, Nathan Jacobs
2020	—	`conf`	Weakly-Supervised Self-Training for Breast Cancer Localization EMBC Gongbo Liang, Xiaoqin Wang, Yu Zhang, Nathan Jacobs
2019	—	`conf`	2D Convolutional Neural Networks for 3D Digital Breast Tomosynthesis Classification. BIBM Yu Zhang, Xiaoqin Wang, Hunter Blanton, Gongbo Liang, Xin Xing, Nathan Jacobs
2019	—	`conf`	Defense-PointNet: Protecting PointNet Against Adversarial Attacks. IEEE BigData Yu Zhang, Gongbo Liang, Tawfiq Salem, Nathan Jacobs
2019	—	`conf`	GANai: Standardizing CT Images using Generative Adversarial Network with Alternative Improvement. ICHI Gongbo Liang, Sajjad Fouladvand, Jie Zhang, Michael A. Brooks, Nathan Jacobs, Jin Chen
2019	—	`conf`	Joint 2D-3D Breast Cancer Classification. BIBM Gongbo Liang, Xiaoqin Wang, Yu Zhang, Xin Xing, Hunter Blanton, Tawfiq Salem, Nathan Jacobs
2018	Misc	`conf`	Enhancing Radiomic Features of CT Images using Generative Adversarial Network with Alternative Improvement. AMIA Gongbo Liang, Jie Zhang, Michael A. Brooks, Jessica Howard, Jin Chen
2016	B	`conf`	Pedestrian detection via a leg-driven physiology framework. ICIP Gongbo Liang, Qi Li, Xiangui Kang
2015	—	`conf`	A geometric framework for stop sign detection. ChinaSIP Qi Li, Gongbo Liang, Yongyi Gong