TN242 97042223多模气体激光纵模线型函数及其频宽的实验观测=Observation of line-shape function and its frequencywidth of longitudinal mode in a multimodegas laser[刊,中]/印建平,方建兴,高伟建（苏州大学物理系.江苏,苏州（21...TN242 97042223多模气体激光纵模线型函数及其频宽的实验观测=Observation of line-shape function and its frequencywidth of longitudinal mode in a multimodegas laser[刊,中]/印建平,方建兴,高伟建（苏州大学物理系.江苏,苏州（215006））,王育竹（中科院上海光机所量子光学开放实验室.上海（201800））//光学学报.—1996,16（6）.—721-726根据多模激光时间相干性g<sup>（1）</sup>（τ）的准周期性特点,提出了一种观测多模激光纵模线型函数及其频宽的新方法—程差2kL法。介绍了测量原理与方法。展开更多
Laser cleaning is a highly nonlinear physical process for solving poor single-modal(e.g., acoustic or vision)detection performance and low inter-information utilization. In this study, a multi-modal feature fusion net...Laser cleaning is a highly nonlinear physical process for solving poor single-modal(e.g., acoustic or vision)detection performance and low inter-information utilization. In this study, a multi-modal feature fusion network model was constructed based on a laser paint removal experiment. The alignment of heterogeneous data under different modals was solved by combining the piecewise aggregate approximation and gramian angular field. Moreover, the attention mechanism was introduced to optimize the dual-path network and dense connection network, enabling the sampling characteristics to be extracted and integrated. Consequently, the multi-modal discriminant detection of laser paint removal was realized. According to the experimental results, the verification accuracy of the constructed model on the experimental dataset was 99.17%, which is 5.77% higher than the optimal single-modal detection results of the laser paint removal. The feature extraction network was optimized by the attention mechanism, and the model accuracy was increased by 3.3%. Results verify the improved classification performance of the constructed multi-modal feature fusion model in detecting laser paint removal, the effective integration of acoustic data and visual image data, and the accurate detection of laser paint removal.展开更多
文摘TN242 97042223多模气体激光纵模线型函数及其频宽的实验观测=Observation of line-shape function and its frequencywidth of longitudinal mode in a multimodegas laser[刊,中]/印建平,方建兴,高伟建（苏州大学物理系.江苏,苏州（215006））,王育竹（中科院上海光机所量子光学开放实验室.上海（201800））//光学学报.—1996,16（6）.—721-726根据多模激光时间相干性g<sup>（1）</sup>（τ）的准周期性特点,提出了一种观测多模激光纵模线型函数及其频宽的新方法—程差2kL法。介绍了测量原理与方法。
基金Project(51875491) supported by the National Natural Science Foundation of ChinaProject(2021T3069) supported by the Fujian Science and Technology Plan STS Project,China。
文摘Laser cleaning is a highly nonlinear physical process for solving poor single-modal(e.g., acoustic or vision)detection performance and low inter-information utilization. In this study, a multi-modal feature fusion network model was constructed based on a laser paint removal experiment. The alignment of heterogeneous data under different modals was solved by combining the piecewise aggregate approximation and gramian angular field. Moreover, the attention mechanism was introduced to optimize the dual-path network and dense connection network, enabling the sampling characteristics to be extracted and integrated. Consequently, the multi-modal discriminant detection of laser paint removal was realized. According to the experimental results, the verification accuracy of the constructed model on the experimental dataset was 99.17%, which is 5.77% higher than the optimal single-modal detection results of the laser paint removal. The feature extraction network was optimized by the attention mechanism, and the model accuracy was increased by 3.3%. Results verify the improved classification performance of the constructed multi-modal feature fusion model in detecting laser paint removal, the effective integration of acoustic data and visual image data, and the accurate detection of laser paint removal.
