A novel method of text representation on hybrid neural networks. - Yanbu Guo; Chen Jin; Weihua Li 006; Chen Ji; Yuan Fang; Yunhao Duan (CISP-BMEI, 2017)

Protein secondary structure prediction improved by recurrent neural networks integrated with two-dimensional convolutional neural networks. - Yanbu Guo; Bingyi Wang; Weihua Li 006; Bei Yang (J. Bioinform. Comput. Biol., 2018)

DeepACLSTM: deep asymmetric convolutional long short-term memory neural models for protein secondary structure prediction. - Yanbu Guo; Weihua Li 006; Bingyi Wang; Huiqing Liu; Dongming Zhou (BMC Bioinform., 2019)

基于贝叶斯网的短文本特征扩展方法 (Short Text Feature Extension Method Based on Bayesian Networks). - Huiqing Liu; Yanbu Guo; Hongling Li; Weihua Li 006 (计算机科学, 2019)

Robust spiking cortical model and total-variational decomposition for multimodal medical image fusion. - Yanyu Liu; Dongming Zhou; Rencan Nie; Ruichao Hou; Zhaisheng Ding; Yanbu Guo; Jinwei Zhou (Biomed. Signal Process. Control., 2020)

DeepANF: A deep attentive neural framework with distributed representation for chromatin accessibility prediction. - Yanbu Guo; Dongming Zhou; Rencan Nie; Xiaoli Ruan; Weihua Li 006 (Neurocomputing, 2020)

Attentive gated neural networks for identifying chromatin accessibility. - Yanbu Guo; Dongming Zhou; Weihua Li 006; Rencan Nie; Ruichao Hou; Chengli Zhou (Neural Comput. Appl., 2020)

VIF-Net: An Unsupervised Framework for Infrared and Visible Image Fusion. - Ruichao Hou; Dongming Zhou; Rencan Nie; Dong Liu 023; Lei Xiong; Yanbu Guo; Chuanbo Yu (IEEE Trans. Computational Imaging, 2020)

Identifying polyadenylation signals with biological embedding via self-attentive gated convolutional highway networks. - Yanbu Guo; Dongming Zhou; Weihua Li 006; Jinde Cao; Rencan Nie; Lei Xiong; Xiaoli Ruan (Appl. Soft Comput., 2021)

UFA-FUSE: A novel deep supervised and hybrid model for multi-focus image fusion. - Yongsheng Zang; Dongming Zhou; Changcheng Wang; Rencan Nie; Yanbu Guo (CoRR, 2021)

Bidirectional LSTM-CRF Attention-based Model for Chinese Word Segmentation. - Chen Jin; Zhuangwei Shi; Weihua Li 006; Yanbu Guo (CoRR, 2021)

Multimodal medical image fusion based on the spectral total variation and local structural patch measurement. - Yanyu Liu; Ruichao Hou; Dongming Zhou; Rencan Nie; Zhaisheng Ding; Yanbu Guo; Li Zhao (Int. J. Imaging Syst. Technol., 2021)

UFA-FUSE: A Novel Deep Supervised and Hybrid Model for Multifocus Image Fusion. - Yongsheng Zang; Dongming Zhou; Changcheng Wang; Rencan Nie; Yanbu Guo (IEEE Trans. Instrum. Meas., 2021)

TSE_Fuse: Two stage enhancement method using attention mechanism and feature-linking model for infrared and visible image fusion. - Yanyu Liu; Dongming Zhou; Rencan Nie; Zhaisheng Ding; Yanbu Guo; Xiaoli Ruan; Weidai Xia; Ruichao Hou (Digit. Signal Process., 2022)

Deep multi-scale Gaussian residual networks for contextual-aware translation initiation site recognition. - Yanbu Guo; Dongming Zhou; Weihua Li 006; Jinde Cao (Expert Syst. Appl., 2022)

Deep Effective k-mer representation learning for polyadenylation signal prediction via co-occurrence embedding. - Yanbu Guo; Hongxue Shen; Weihua Li 006; Chaoyang Li 001; Chen Jin (Knowl. Based Syst., 2022)

Gated residual neural networks with self-normalization for translation initiation site recognition. - Yanbu Guo; Dongming Zhou; Jinde Cao; Rencan Nie; Xiaoli Ruan; Yanyu Liu (Knowl. Based Syst., 2022)

Context-aware dynamic neural computational models for accurate Poly(A) signal prediction. - Yanbu Guo; Chaoyang Li 001; Dongming Zhou; Jinde Cao; Hui Liang 004 (Neural Networks, 2022)

Rethinking Low-Light Enhancement via Transformer-GAN. - Shaoliang Yang; Dongming Zhou; Jinde Cao; Yanbu Guo (IEEE Signal Process. Lett., 2022)

LightingNet: An Integrated Learning Method for Low-Light Image Enhancement. - Shaoliang Yang; Dongming Zhou; Jinde Cao; Yanbu Guo (IEEE Trans. Computational Imaging, 2023)

Learning spatiotemporal embedding with gated convolutional recurrent networks for translation initiation site prediction. - Weihua Li 006; Yanbu Guo; Bingyi Wang; Bei Yang (Pattern Recognit., 2023)

Variational gated autoencoder-based feature extraction model for inferring disease-miRNA associations based on multiview features. - Yanbu Guo; Dongming Zhou; Xiaoli Ruan; Jinde Cao (Neural Networks, 2023)

EPIC: An epidemiological investigation of COVID-19 dataset for Chinese named entity recognition. - Pu Li; Guohao Zhou; Yanbu Guo; Suzhi Zhang; Yuncheng Jiang; Yong Tang 001 (Inf. Process. Manag., 2024)

Context-Aware Poly(A) Signal Prediction Model via Deep Spatial-Temporal Neural Networks. - Yanbu Guo; Dongming Zhou; Pu Li; Chaoyang Li 001; Jinde Cao (IEEE Trans. Neural Networks Learn. Syst., 2024)

Deep gate information bottleneck-based prediction model for complex disease-related micro-ribonucleic acids via heterogeneous biological networks. - Yanbu Guo; Yiyang Xin; Jinde Cao; Yaoli Xu; Dongming Zhou (Eng. Appl. Artif. Intell., 2025)