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Multi-level transfer learning for improving the performance of deep neural networks: Theory and practice from the tasks of facial emotion recognition and named entity recognition.

, and . Appl. Soft Comput., (2021)

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Multi-level transfer learning for improving the performance of deep neural networks: Theory and practice from the tasks of facial emotion recognition and named entity recognition., and . Appl. Soft Comput., (2021)Applying attention-based BiLSTM and technical indicators in the design and performance analysis of stock trading strategies., , , , , and . Neural Comput. Appl., 34 (16): 13267-13279 (2022)Exploring the distributed learning on federated learning and cluster computing via convolutional neural networks., , and . Neural Comput. Appl., 36 (5): 2141-2153 (February 2024)Using a self-organizing neural network for wafer defect inspection., , and . SMC (5), page 4312-4317. IEEE, (2004)Improving of Segmental LMR-Mapping Based Voice Conversion Method., and . IJCLCLP, (2013)An Unsupervised Self-Organizing Neural Network for Automatic Semiconductor Wafer Defect Inspection., , and . ICRA, page 3000-3005. IEEE, (2005)Using Variation Theory as a Guiding Principle in an OOP Assisted Syntax Correction Learning System., , , and . Int. J. Emerg. Technol. Learn., 15 (14): 35-52 (2020)A Study on Using Transfer Learning to Improve BERT Model for Emotional Classification of Chinese Lyrics., , , and . ROCLING, page 13-17. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP), (2021)A Study on Using Different Audio Lengths in Transfer Learning for Improving Chainsaw Sound Recognition., and . ROCLING, page 67-74. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP), (2022)基於音段式LMR 對映之語音轉換方法的改進 (Improving of Segmental LMR-Mapping Based Voice Conversion Methods) In Chinese., and . ROCLING, Association for Computational Linguistics and Chinese Language Processing (ACLCLP), Taiwan, (2013)