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Neural Networks 2023: all accepted papers

643 papers · page 1 of 7 · the most cited first · ← Neural Networks 2023

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  1. A survey on few-shot class-incremental learning ↗Songsong Tian, Lusi Li, Weijun Li et al.214 citations
  2. MonkeyNet: A robust deep convolutional neural network for monkeypox disease detection and classification ↗Diponkor Bala, Md. Shamim Hossain, Md. Alamgir Hossain et al.191 citations
  3. CVANet: Cascaded visual attention network for single image super-resolution ↗Weidong Zhang, Wenyi Zhao, Jia Li et al.148 citations
  4. Dual-domain strip attention for image restoration ↗Yuning Cui, Alois Knoll147 citations
  5. A transformer-based deep neural network model for SSVEP classification ↗Jianbo Chen, Yangsong Zhang, Yudong Pan et al.131 citations
  6. A survey on neural-symbolic learning systems ↗Dongran Yu, Bo Xiong Yang, Dayou Liu et al.112 citations
  7. A survey on cancer detection via convolutional neural networks: Current challenges and future directions ↗Pallabi Sharma, Deepak Ranjan Nayak, Bunil Kumar Balabantaray et al.94 citations
  8. Boundary uncertainty aware network for automated polyp segmentation ↗Guanghui Yue, Guibin Zhuo, Weiqing Yan et al.87 citations
  9. GT-LSTM: A spatio-temporal ensemble network for traffic flow prediction ↗Yong Jian Luo, Jianying Zheng, Xiang Wang et al.83 citations
  10. Continual Object Detection: A review of definitions, strategies, and challenges ↗Angelo Garangau Menezes, Gustavo de Moura, Cézanne Alves et al.74 citations
  11. LFighter: Defending against the label-flipping attack in federated learning ↗Najeeb Jebreel, Josep Domingo‐Ferrer, David Sánchez et al.74 citations
  12. CrimeNet: Neural Structured Learning using Vision Transformer for violence detection ↗Fernando J. Rendón-Segador, Juan A. Álvarez-García, Jose L. Salazar González et al.65 citations
  13. SCL: Self-supervised contrastive learning for few-shot image classification ↗Jit Yan Lim, Jit Yan Lim, Kian Ming Lim et al.65 citations
  14. Long short-term memory with activation on gradient ↗Chuan Qin, Liangming Chen, Zangtai Cai et al.62 citations
  15. Quantum recurrent neural networks for sequential learning ↗Yanan Li, Zhimin Wang, Rongbing Han et al.60 citations
  16. Partial label learning: Taxonomy, analysis and outlook ↗Yingjie Tian, Xiaotong Yu, Saiji Fu58 citations
  17. Unsupervised feature selection based on variance–covariance subspace distance ↗Saeed Karami, Farid Saberi-Movahed, Prayag Tiwari et al.57 citations
  18. A multi-modal deep neural network for multi-class liver cancer diagnosis ↗Rayyan Azam Khan, Minghan Fu, Brent Burbridge et al.54 citations
  19. SCADA securing system using deep learning to prevent cyber infiltration ↗Sayawu Yakubu Diaba, Theophilus Anafo, Lord Anertei Tetteh et al.54 citations
  20. Balance guided incomplete multi-view spectral clustering ↗Lilei Sun, Jie Wen, Chengliang Liu et al.52 citations
  21. Deep Kernel Principal Component Analysis for multi-level feature learning ↗Francesco Tonin, Qinghua Tao, Panagiotis Patrinos et al.50 citations
  22. CLAD: A realistic Continual Learning benchmark for Autonomous Driving ↗Eli Verwimp, Kuo Yang, Sarah Parisot et al.49 citations
  23. Joint learning of feature and topology for multi-view graph convolutional network ↗Yuhong Chen, Zhihao Wu, Zhaoliang Chen et al.48 citations
  24. Graph contrastive learning with implicit augmentations ↗Huidong Liang, Xingjian Du, Bilei Zhu et al.47 citations
  25. Multi-scale feature selection network for lightweight image super-resolution ↗Minghong Li, Yuqian Zhao, Fan Zhang et al.46 citations
  26. Retinal vessel segmentation via a Multi-resolution Contextual Network and adversarial learning ↗Tariq Mahmood Khan, Syed S. Naqvi, Antonio Robles‐Kelly et al.46 citations
  27. Trainable Spiking-YOLO for low-latency and high-performance object detection ↗Mengwen Yuan, Chengjun Zhang, Ziming Wang et al.45 citations
  28. EQNAS: Evolutionary Quantum Neural Architecture Search for Image Classification ↗Yangyang Li, Ruijiao Liu, Xiaobin Hao et al.44 citations
  29. Stereoscopic scalable quantum convolutional neural networks ↗Hankyul Baek, Won Joon Yun, Soohyun Park et al.44 citations

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