The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results ...The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor composed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experiments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map estimation.展开更多
In order to address the issue of sensor configuration redundancy in intelligent driving,this paper constructs a multi-objective optimization model that considers cost,coverage ability,and perception performance.And th...In order to address the issue of sensor configuration redundancy in intelligent driving,this paper constructs a multi-objective optimization model that considers cost,coverage ability,and perception performance.And then,combining a specific set of parameters,the NSGA-II algorithm is used to solve the multi-objective model established in this paper,and a Pareto front containing 24 typical configuration schemes is extracted after considering empirical constraints.Finally,using the decision preference method proposed in this paper that combines subjective and objective factors,decision scores are calculated and ranked for various configuration schemes from both cost and performance preferences.The research results indicate that the multi-objective optimization model established in this paper can screen and optimize various configuration schemes from the optimal principle of the vehicle,and the optimized configuration schemes can be quantitatively ranked to obtain the decision results for the vehicle under different preference tendencies.展开更多
To Meet the requirements of multi-sensor data fusion in diagnosis for complex equipment systems,a novel, fuzzy similarity-based data fusion algorithm is given. Based on fuzzy set theory, it calculates the fuzzy simila...To Meet the requirements of multi-sensor data fusion in diagnosis for complex equipment systems,a novel, fuzzy similarity-based data fusion algorithm is given. Based on fuzzy set theory, it calculates the fuzzy similarity among a certain sensor's measurement values and the multiple sensor's objective prediction values to determine the importance weigh of each sensor,and realizes the multi-sensor diagnosis parameter data fusion.According to the principle, its application software is also designed. The applied example proves that the algorithm can give priority to the high-stability and high -reliability sensors and it is laconic ,feasible and efficient to real-time circumstance measure and data processing in engine diagnosis.展开更多
当前,全球科技创新呈现高速发展和高度融合的态势。准确识别出颠覆性技术主题以推动全面创新已成为科学技术发展和经济增长的关键动力。然而,传统的颠覆性技术主题识别方法主要依赖于单一模态数据,存在一定的局限性。本文基于CLIP(contr...当前,全球科技创新呈现高速发展和高度融合的态势。准确识别出颠覆性技术主题以推动全面创新已成为科学技术发展和经济增长的关键动力。然而,传统的颠覆性技术主题识别方法主要依赖于单一模态数据,存在一定的局限性。本文基于CLIP(contrastive language-image pre-training)和LDAGV(linear discriminant analysis&global vectors for word representation)模型构建新闻文本与图像特征融合向量,通过k-means聚类迭代并结合3个颠覆性技术主题指标进行筛选,实现了多模态信息的融合以及主题的精准识别。以新能源领域为例,验证了该模型在颠覆性技术主题识别方面的可行性和有效性。与其他单一模态模型相比,多模态信息融合模型在颠覆性技术主题识别方面更具优势。展开更多
基金the National Key R&D Program of China(2018AAA0103103).
文摘The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor composed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experiments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map estimation.
文摘In order to address the issue of sensor configuration redundancy in intelligent driving,this paper constructs a multi-objective optimization model that considers cost,coverage ability,and perception performance.And then,combining a specific set of parameters,the NSGA-II algorithm is used to solve the multi-objective model established in this paper,and a Pareto front containing 24 typical configuration schemes is extracted after considering empirical constraints.Finally,using the decision preference method proposed in this paper that combines subjective and objective factors,decision scores are calculated and ranked for various configuration schemes from both cost and performance preferences.The research results indicate that the multi-objective optimization model established in this paper can screen and optimize various configuration schemes from the optimal principle of the vehicle,and the optimized configuration schemes can be quantitatively ranked to obtain the decision results for the vehicle under different preference tendencies.
文摘To Meet the requirements of multi-sensor data fusion in diagnosis for complex equipment systems,a novel, fuzzy similarity-based data fusion algorithm is given. Based on fuzzy set theory, it calculates the fuzzy similarity among a certain sensor's measurement values and the multiple sensor's objective prediction values to determine the importance weigh of each sensor,and realizes the multi-sensor diagnosis parameter data fusion.According to the principle, its application software is also designed. The applied example proves that the algorithm can give priority to the high-stability and high -reliability sensors and it is laconic ,feasible and efficient to real-time circumstance measure and data processing in engine diagnosis.
文摘当前,全球科技创新呈现高速发展和高度融合的态势。准确识别出颠覆性技术主题以推动全面创新已成为科学技术发展和经济增长的关键动力。然而,传统的颠覆性技术主题识别方法主要依赖于单一模态数据,存在一定的局限性。本文基于CLIP(contrastive language-image pre-training)和LDAGV(linear discriminant analysis&global vectors for word representation)模型构建新闻文本与图像特征融合向量,通过k-means聚类迭代并结合3个颠覆性技术主题指标进行筛选,实现了多模态信息的融合以及主题的精准识别。以新能源领域为例,验证了该模型在颠覆性技术主题识别方面的可行性和有效性。与其他单一模态模型相比,多模态信息融合模型在颠覆性技术主题识别方面更具优势。
