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Page 28 of 28                        Zhang et al. J Mater Inf 2024;4:34  https://dx.doi.org/10.20517/jmi.2024.64

               79.      Qiao Y, Zhang Q, Qi Y, Wan T, Yang L, Yu X. A waste classification model in low-illumination scenes based on ConvNeXt. Resour
                   Conserv Recy 2023;199:107274.  DOI
               80.      Jablonka KM, Ai Q, Al-Feghali A, et al. 14 examples of how LLMs can transform materials science and chemistry: a reflection on a
                   large language model hackathon. Digit Discov 2023;2:1233-50.  DOI
               81.      Choi J, Lee B. Accelerating materials language processing with large language models. Commun Mater 2024;5:449.  DOI
               82.      Zang Y, Li W, Han J, Zhou K, Loy CC. Contextual object detection with multimodal large language models. Int J Comput Vis 2024.
                   DOI
               83.      Mahowald K, Ivanova AA, Blank IA, Kanwisher N, Tenenbaum JB, Fedorenko E. Dissociating language and thought in large
                   language models. Trends Cogn Sci 2024;28:517-40.  DOI  PubMed  PMC
               84.      Wang H, Li J, Wu H, Hovy E, Sun Y. Pre-trained language models and their applications. Engineering 2023;25:51-65.  DOI
               85.      Hu L, Liu Z, Zhao Z, Hou L, Nie L, Li J. A survey of knowledge enhanced pre-trained language models. IEEE Trans Knowl Data Eng
                   2024;36:1413-30.  DOI
               86.      Lai Z, Wu T, Fei X, Ling Q. BERT4ST:: fine-tuning pre-trained large language model for wind power forecasting. Energ Convers
                   Manage 2024;307:118331.  DOI
               87.      Cook A, Karakuş O. LLM-commentator: novel fine-tuning strategies of large language models for automatic commentary generation
                   using football event data. Knowl Based Syst 2024;300:112219.  DOI
               88.      Zhang Z, Wen G, Chen S. Weld image deep learning-based on-line defects detection using convolutional neural networks for Al alloy
                   in robotic arc welding. J Manuf Process 2019;45:208-16.  DOI
               89.      Yang X, Zhang Y, Lv W, Wang D. Image recognition of wind turbine blade damage based on a deep learning model with transfer
                   learning and an ensemble learning classifier. Renew Energ 2021;163:386-97.  DOI
               90.      Balado J, Sousa R, Díaz-Vilariño L, Arias P. Transfer learning in urban object classification: online images to recognize point clouds.
                   Automat Constr 2020;111:103058.  DOI
               91.      Deng J, Dong W, Socher R, Li LJ, Li K, Li FF. Imagenet: a large-scale hierarchical image database. In: 2009 IEEE Conference on
                   Computer Vision and Pattern Recognition; 2009 Jun 20-25; Miami, USA. IEEE; 2009. pp. 248-55.  DOI
               92.      Husnain M, Missen MMS, Mumtaz S, Luqman MM, Coustaty M, Ogier J. Visualization of high-dimensional data by pairwise fusion
                   matrices using t-SNE. Symmetry 2019;11:107.  DOI
               93.      Moon H, Na S. Optimum design based on mathematical model and neural network to predict weld parameters for fillet joints. J Manuf
                   Syst 1997;16:13-23.  DOI
               94.      Gao Y, Hao K, Xu L, et al. Microstructure homogeneity and mechanical properties of laser-arc hybrid welded AZ31B magnesium
                   alloy. J Magnes Alloy 2024;12:1986-95.  DOI
               95.      Geng P, Ma H, Wang M, et al. Dissimilar linear friction welding of Ni-based superalloys. Int J Mach Tool Manu 2023;191:104062.
                   DOI
               96.      Kim I, Son K, Yang Y, Yaragada P. Sensitivity analysis for process parameters in GMA welding processes using a factorial design
                   method. Int J Mach Tool Manu 2003;43:763-9.  DOI
               97.      Cook GE. Robotic arc welding: research in sensory feedback control. IEEE Trans Ind Electron 1983;IE-30:252-68.  DOI
               98.      Nie L, Lin C, Liao K, Liu S, Zhao Y. Unsupervised deep image stitching: reconstructing stitched features to images. IEEE Trans
                   Image Process 2021;30:6184-97.  DOI
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