A Model, called 'Entity-Roles' is proposed in this paper in which the world of Interest is viewed as some mathematical structure. With respect to this structure, a First order (three-valued) Logic Language is ...A Model, called 'Entity-Roles' is proposed in this paper in which the world of Interest is viewed as some mathematical structure. With respect to this structure, a First order (three-valued) Logic Language is constructured.Any world to be modelled can be logically specified in this Language. The integrity constraints on the database and the deducing rules within the Database world are derived from the proper axioms of the world being modelled.展开更多
文摘A Model, called 'Entity-Roles' is proposed in this paper in which the world of Interest is viewed as some mathematical structure. With respect to this structure, a First order (three-valued) Logic Language is constructured.Any world to be modelled can be logically specified in this Language. The integrity constraints on the database and the deducing rules within the Database world are derived from the proper axioms of the world being modelled.
基金Supported by National Basic Research Program of China（973 Program）（2013CB035500） National Natural Science Foundation of China（61233004,61221003,61074061）+1 种基金 International Cooperation Program of Shanghai Science and Technology Commission （12230709600） the Higher Education Research Fund for the Doctoral Program of China（20120073130006）
文摘近年来,随着羊只养殖向大规模和精细化的方向发展,羊场对智能化管理的需求日益增加。因此,精准的个体识别和行为监测变得尤为重要,对多目标跟踪(Multiple object tracking, MOT)算法的准确性提出了更高要求。然而,现有的MOT算法在目标遮挡和动态场景下的性能仍不理想。本文提出两种跟踪线索:深度调制交并比(Depth modulated intersection over union, DIoU)和轨迹方向建模(Tracklet direction modeling, TDM),旨在补充交并比(Intersection over union, IoU)线索,提高多目标跟踪的精准度和鲁棒性。DIoU线索通过引入目标的深度信息改进了传统的IoU计算方法。TDM聚焦于目标的运动趋势,预测其未来的移动方向。本文将DIoU和TDM跟踪线索集成到BoT-SORT算法中,形成改进的多目标跟踪算法。在两个私有数据集上,改进算法相比基线方法,MOTA(Multiple object tracking accuracy)指标分别提高1.6、1.7个百分点,IDF1(Identification F1 score)指标分别提高1.9、1.0个百分点。结果显示,改进算法在复杂场景中的跟踪连续性和准确性显著提升。
