An Auction Approach to Resource Allocation in OFDM-Based Cognitive Radio Networks. - Lihong Cao; Wenjun Xu 001; Jiaru Lin; Kai Niu 001; Zhiqiang He 001 (VTC Spring, 2012)

Social influence modeling using information theory in mobile social networks. - Sancheng Peng; Aimin Yang 002; Lihong Cao; Shui Yu 001; Dongqing Xie (Inf. Sci., 2017)

Predropout & Inhibition: A Brain-Inspired Method for Convolutional Neural Network. - Wenjie Chen; Fengtong Du; Ye Wang 011; Lihong Cao (CISP-BMEI, 2018)

Predicting spikes with artificial neural network. - Lihong Cao; Jiamin Shen; Lei Wang; Ye Wang 011 (Sci. China Inf. Sci., 2018)

Influence analysis in social networks: A survey. - Sancheng Peng; Yongmei Zhou; Lihong Cao; Shui Yu 001; Jianwei Niu 002; Weijia Jia 001 (J. Netw. Comput. Appl., 2018)

Implementation of Hodgkin-Huxley Spiking Neuron Model Using FPGA. - Zexuan Yi; Wenlong Fu; Lihong Cao (ICCT, 2019)

A Survey of Emotion Analysis in Text Based on Deep Learning. - Lihong Cao; Sancheng Peng; Pengfei Yin; Yongmei Zhou; Aimin Yang 002; Xinguang Li (iSCI, 2020)

Challenges and Trends of Android Malware Detection in the Era of Deep Learning. - Sancheng Peng; Lihong Cao; Yongmei Zhou; Jianguo Xie; Pengfei Yin; Jianli Mo (iSCI, 2020)

A biological plausible audio-visual integration model for continual lifelong learning. - Wenjie Chen; Fengtong Du; Ye Wang 011; Lihong Cao (CoRR, 2020)

Learning How to Zoom In: Weakly Supervised ROI-Based-DAM for Fine-Grained Visual Classification. - Wenjie Chen; Shuang Ran; Tian Wang; Lihong Cao (ICANN (2), 2021)

Implementation of Multi-compartment Neuron Model with Synaptic Plasticity Using FPGA. - Yiwen Ding; Wenlong Fu; Lihong Cao (ICCT, 2021)

A Biologically Plausible Audio-Visual Integration Model for Continual Learning. - Wenjie Chen; Fengtong Du; Ye Wang 011; Lihong Cao (IJCNN, 2021)

DRNet: A Deep Neural Network With Multi-Layer Residual Blocks Improves Image Denoising. - Jiahong Zhang; Yonggui Zhu; Wenyi Li; Wenlong Fu; Lihong Cao (IEEE Access, 2021)

A Simplified Plasticity Model Based on Synaptic Tagging and Capture Theory: Simplified STC. - Yiwen Ding; Ye Wang 011; Lihong Cao (Frontiers Comput. Neurosci., 2021)

Predicting Spike Features of Hodgkin-Huxley-Type Neurons With Simple Artificial Neural Network. - Tian Wang; Ye Wang 011; Jiamin Shen; Lei Wang; Lihong Cao (Frontiers Comput. Neurosci., 2021)

Aspect-level sentiment analysis using context and aspect memory network. - Yanxia Lv; Fangna Wei; Lihong Cao; Sancheng Peng; Jianwei Niu 002; Shui Yu 001; Cuirong Wang (Neurocomputing, 2021)

A Multi-Head Convolutional Neural Network with Multi-Path Attention Improves Image Denoising. - Jiahong Zhang; Meijun Qu; Ye Wang 011; Lihong Cao (PRICAI (3), 2022)

$p$-Norm Broad Learning for Negative Emotion Classification in Social Networks. - Guanghao Chen; Sancheng Peng; Rong Zeng; Zhongwang Hu; Lihong Cao; Yongmei Zhou; Zhouhao Ouyang; Xiangyu Nie (Big Data Min. Anal., 2022)

A survey on deep learning for textual emotion analysis in social networks. - Sancheng Peng; Lihong Cao; Yongmei Zhou; Zhouhao Ouyang; Aimin Yang 002; Xinguang Li; Weijia Jia 001; Shui Yu 001 (Digit. Commun. Networks, 2022)

NHNet: A non-local hierarchical network for image denoising. - Jiahong Zhang; Lihong Cao; Tian Wang; Wenlong Fu; Weiheng Shen (IET Image Process., 2022)

BIFRNet: A Brain-Inspired Feature Restoration DNN for Partially Occluded Image Recognition. - Jiahong Zhang; Lihong Cao; Qiuxia Lai; Bingyao Li; Yunxiao Qin (AAAI, 2023)

Extracting the Brain-Like Representation by an Improved Self-Organizing Map for Image Classification. - Jiahong Zhang; Lihong Cao; Moning Zhang; Wenlong Fu (ICASSP, 2023)

Research of Multidimensional Adversarial Examples in LLMs for Recognizing Ethics and Security Issues. - Kainan Liu; Yifan Li; Lihong Cao; Danni Tu; Zhi Fang; Yusong Zhang (ICCSE (3), 2023)

Multi-source domain adaptation method for textual emotion classification using deep and broad learning. - Sancheng Peng; Rong Zeng; Lihong Cao; Aimin Yang; Jianwei Niu 002; Chengqing Zong; Guodong Zhou (Knowl. Based Syst., 2023)

EEG-based visual stimuli classification via reusable LSTM. - Yaling Deng; Shuo Ding; Wenyi Li; Qiuxia Lai; Lihong Cao (Biomed. Signal Process. Control., 2023)

A Brain-inspired Method for Occluded 3D Object Recognition. - Zining Wan; Jiahong Zhang; Lihong Cao (IJCNN, 2024)

Prompt-based Continual Learning for Extending Pretrained CLIP Models' Knowledge. - Li Jiao; Lihong Cao; Tian Wang (MMAsia, 2024)

Textual emotion classification using MPNet and cascading broad learning. - Lihong Cao; Rong Zeng; Sancheng Peng; Aimin Yang 002; Jianwei Niu 002; Shui Yu 001 (Neural Networks, 2024)

Self-Supervised Video Representation Learning via Capturing Semantic Changes Indicated by Saccades. - Qiuxia Lai; Ailing Zeng; Ye Wang 011; Lihong Cao; Yu Li 007; Qiang Xu 001 (IEEE Trans. Circuits Syst. Video Technol., 2024)

A survey on textual emotion cause extraction in social networks. - Sancheng Peng; Lihong Cao; Guo-Jun Wang 001; Zhouhao Ouyang; Yongmei Zhou; Shui Yu 001 (Digit. Commun. Networks, 2025)

Enabling scale and rotation invariance in convolutional neural networks with retina like transformation. - Jiahong Zhang; Guoqi Li; Qiaoyi Su; Lihong Cao; Yonghong Tian 001; Bo Xu 002 (Neural Networks, 2025)