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ORCIDNeural Networks, Volume 170
Volume 170, 2024
- Onur Can Kurban
, Tülay Yildirim:
A comparative analysis of multi-biometrics performance in human and action recognition using silhouette thermal-face and skeletal data. 1-17 - Konrad A. Ciecierski, Tomasz Mandat:
Classification of DBS microelectrode recordings using a residual neural network with attention in the temporal domain. 18-31 - José de Jesús Rubio, Mario Alberto Hernandez, Francisco Javier Rosas, Eduardo Orozco, Ricardo Balcazar, Jaime Pacheco:
Genetic high-gain controller to improve the position perturbation attenuation and compact high-gain controller to improve the velocity perturbation attenuation in inverted pendulums. 32-45 - Minghao Hui, Xiaoyang Liu, Song Zhu, Jinde Cao:
Event-triggered impulsive cluster synchronization of coupled reaction-diffusion neural networks and its application to image encryption. 46-54 - Qing Wan, Siu Wun Cheung, Yoonsuck Choe:
AdjointBackMapV2: Precise reconstruction of arbitrary CNN unit's activation via adjoint operators. 55-71 - Giorgio Gosti, Edoardo Milanetti, Viola Folli, Francesco de Pasquale, Marco Leonetti, Maurizio Corbetta, Giancarlo Ruocco, Stefania Della Penna:
A recurrent Hopfield network for estimating meso-scale effective connectivity in MEG. 72-93 - Alexander Wikner, Joseph Harvey, Michelle Girvan, Brian R. Hunt, Andrew Pomerance, Thomas M. Antonsen Jr., Edward Ott:
Stabilizing machine learning prediction of dynamics: Novel noise-inspired regularization tested with reservoir computing. 94-110 - Najeeb Moharram Jebreel, Josep Domingo-Ferrer, David Sánchez, Alberto Blanco-Justicia:
LFighter: Defending against the label-flipping attack in federated learning. 111-126 - Hao Deng, Chuandong Li, Fei Chang, Yinuo Wang:
Mean square exponential stabilization analysis of stochastic neural networks with saturated impulsive input. 127-135 - Jinhao Li, Huying Li, Yuan Zhang, Zhiqiang Wang, Sheng Zhu, Xuanya Li, Kai Hu, Xieping Gao:
MCNet: A multi-level context-aware network for the segmentation of adrenal gland in CT images. 136-148 - Hoang Phuc Hau Luu, Hoai Minh Le, Hoai An Le Thi:
Markov chain stochastic DCA and applications in deep learning with PDEs regularization. 149-166 - Vishruth B. Gowda, M. T. Gopalakrishna, Megha J, Mohankumar Shilpa:
Foreground segmentation network using transposed convolutional neural networks and up sampling for multiscale feature encoding. 167-175 - Zhiqiang Bao, Zhenhua Huang, Jianping Gou, Lan Du, Kang Liu, Jingtao Zhou, Yunwen Chen:
Teacher-student complementary sample contrastive distillation. 176-189 - Guobin Shen, Dongcheng Zhao, Yi Zeng:
Exploiting nonlinear dendritic adaptive computation in training deep Spiking Neural Networks. 190-201 - Feng Lin, Huaqing Zhang, Jian Wang, Jun Wang:
Unsupervised image enhancement under non-uniform illumination based on paired CNNs. 202-214 - Gorka Azkune, Ander Salaberria, Eneko Agirre:
Grounding spatial relations in text-only language models. 215-226 - Qinghua Wang, Ziwei Li, Shuqi Zhang, Nan Chi, Qionghai Dai:
A versatile Wavelet-Enhanced CNN-Transformer for improved fluorescence microscopy image restoration. 227-241 - Haozhong Wang, Hua Yu, Qiang Zhang:
Human-Object Interaction detection via Global Context and Pairwise-level Fusion Features Integration. 242-253 - Álvaro S. Hervella, José Rouco, Jorge Novo, Marcos Ortega:
Multi-Adaptive Optimization for multi-task learning with deep neural networks. 254-265 - Xinyu Fu, Irwin King:
MECCH: Metapath Context Convolution-based Heterogeneous Graph Neural Networks. 266-275 - Can Liu, Kaige Wang, Qing Li, Fazhan Zhao, Kun Zhao, Hongtu Ma:
Powerful-IoU: More straightforward and faster bounding box regression loss with a nonmonotonic focusing mechanism. 276-284 - Zhenyi Wang, Pengfei Yang, Linwei Hu, Bowen Zhang, Chengmin Lin, Wenkai Lv, Quan Wang:
SLAPP: Subgraph-level attention-based performance prediction for deep learning models. 285-297 - Ning Zhang, Long Yu, Dezhi Zhang, Weidong Wu, Shengwei Tian, Xiaojing Kang, Min Li:
CT-Net: Asymmetric compound branch Transformer for medical image segmentation. 298-311 - Xingfu Wang, Yu Wang, Wenxia Qi, Delin Kong, Wei Wang:
BrainGridNet: A two-branch depthwise CNN for decoding EEG-based multi-class motor imagery. 312-324 - Teng Cheng, Lei Sun, Junning Zhang, Jinling Wang, Zhanyang Wei:
A start-stop points CenterNet for wideband signals detection and time-frequency localization in spectrum sensing. 325-336 - Huanjie Tao, Qianyue Duan:
Hierarchical attention network with progressive feature fusion for facial expression recognition. 337-348 - Naoko Koide-Majima, Shinji Nishimoto, Kei Majima:
Mental image reconstruction from human brain activity: Neural decoding of mental imagery via deep neural network-based Bayesian estimation. 349-363 - Sergey Zinchenko, Dmitry Lishudi:
Star algorithm for neural network ensembling. 364-375 - Victor R. Barradas, Yasuharu Koike, Nicolas Schweighofer:
Theoretical limits on the speed of learning inverse models explain the rate of adaptation in arm reaching tasks. 376-389 - Guanghui Yue, Guibin Zhuo, Weiqing Yan, Tianwei Zhou, Chang Tang, Peng Yang, Tianfu Wang:
Boundary uncertainty aware network for automated polyp segmentation. 390-404 - Wenming Wu, Xiaoke Ma, Quan Wang, Maoguo Gong, Quanxue Gao:
Learning deep representation and discriminative features for clustering of multi-layer networks. 405-416 - Qinyi Deng, Yong Guo, Zhibang Yang, Haolin Pan, Jian Chen:
Boosting semi-supervised learning with Contrastive Complementary Labeling. 417-426 - Wenxu Wang, Zhenbo Li, Weiran Li:
Graph embedding-based heterogeneous domain adaptation with domain-invariant feature learning and distributional order preserving. 427-440 - Yiyang Yin, Shuangling Luo, Jun Zhou, Liang Kang, Calvin Yu-Chian Chen:
LDCNet: Lightweight dynamic convolution network for laparoscopic procedures image segmentation. 441-452 - Tongfeng Sun, Xiurui Wang, Zhongnian Li, Shifei Ding:
Feature-wise scaling and shifting: Improving the generalization capability of neural networks through capturing independent information of features. 453-467 - Enmin Song, Bangcheng Zhan, Hong Liu:
Combining external-latent attention for medical image segmentation. 468-477 - Jiahao Yu, Xin Gao, Baofeng Li, Feng Zhai, Jiansheng Lu, Bing Xue, Shiyuan Fu, Chun Xiao:
A filter-augmented auto-encoder with learnable normalization for robust multivariate time series anomaly detection. 478-493 - Lin Xiao, Penglin Cao, Zidong Wang, Sai Liu:
A novel fixed-time error-monitoring neural network for solving dynamic quaternion-valued Sylvester equations. 494-505 - A. Stephen, R. Karthikeyan, Chandran Sowmiya, Ramachandran Raja, Ravi P. Agarwal:
Sampled-data controller scheme for multi-agent systems and its Application to circuit network. 506-520 - Fushuo Huo, Ziming Liu, Jingcai Guo, Wenchao Xu, Song Guo:
UTDNet: A unified triplet decoder network for multimodal salient object detection. 521-534 - Yueyue Yao, Jianghong Ma, Shanshan Feng, Yunming Ye:
SVD-AE: An asymmetric autoencoder with SVD regularization for multivariate time series anomaly detection. 535-547 - Huayue Cai, Long Lan, Jing Zhang, Xiang Zhang, Yibing Zhan, Zhigang Luo:
IoUformer: Pseudo-IoU prediction with transformer for visual tracking. 548-563 - Chenxin Xu, Yuxi Wei, Bohan Tang, Sheng Yin, Ya Zhang, Siheng Chen, Yanfeng Wang:
Dynamic-group-aware networks for multi-agent trajectory prediction with relational reasoning. 564-577 - Francesco Tonin, Qinghua Tao, Panagiotis Patrinos, Johan A. K. Suykens:
Deep Kernel Principal Component Analysis for multi-level feature learning. 578-595 - Qinchen Yang, Fukai Zhang, Qinghua Sun, Cong Wang:
Dynamic learning from adaptive neural control for full-state constrained strict-feedback nonlinear systems. 596-609 - Delin Guo, Lan Tang, Xinggan Zhang, Ying-Chang Liang:
An off-policy multi-agent stochastic policy gradient algorithm for cooperative continuous control. 610-621 - Weidong Zhang, Wenyi Zhao, Jia Li, Peixian Zhuang, Hai-Han Sun, Yibo Xu, Chongyi Li:
CVANet: Cascaded visual attention network for single image super-resolution. 622-634 - Chu Myaet Thwal, Minh N. H. Nguyen, Ye Lin Tun, Seong Tae Kim, My T. Thai, Choong Seon Hong:
OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning. 635-649
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