Reintroduction is an important strategy to restore or re-establish wild populations of endangered species.Pre-release training is a necessary step to ensure postreintroduction survival.However,studies reported contrad...Reintroduction is an important strategy to restore or re-establish wild populations of endangered species.Pre-release training is a necessary step to ensure postreintroduction survival.However,studies reported contradicting outcomes after pre-release training of juveniles and adults.This study used farmed and feral American mink(Neovison vison)to analyze the influence of captive breeding on the morphology,structure and efficiency of the two major hindlimb levers,the femur and tibia pivoted by hip and knee joints that are essential for locomotion.Results showed that captive breeding did not alter the sexual dimorphism of the two levers that are related to survival in the wild.Captive-bred mink showed slightly altered morphology of the femur and fundamental structure of the hindlimb levers that improved efficiency,but this resulted in reduction of performance related to foraging in both terrestrial and aquatic environments,especially for females.These findings suggest that reintroduction of mustelid as exampled by the mink here should focus on juveniles because the skeletal alterations associated with captive rearing were recorded only among adults and are irreversible in adulthood.In contrast,captive-reared juveniles showed no skeletal alterations and would be expected to recovery from any atrophy of the muscular system caused by captive rearing for shorter durations.Our results support the application of pre-release training of juveniles in enriched environments as a method for alleviating structural alteration of appendages and enhancing locomotion to increase survival probability in complex habitats.展开更多
For some important object recognition applications such as intelligent robots and unmanned driving, images are collected on a consecutive basis and associated among themselves, besides, the scenes have steady prior fe...For some important object recognition applications such as intelligent robots and unmanned driving, images are collected on a consecutive basis and associated among themselves, besides, the scenes have steady prior features. Yet existing technologies do not take full advantage of this information. In order to take object recognition further than existing algorithms in the above application, an object recognition method that fuses temporal sequence with scene priori information is proposed. This method first employs YOLOv3 as the basic algorithm to recognize objects in single-frame images, then the DeepSort algorithm to establish association among potential objects recognized in images of different moments, and finally the confidence fusion method and temporal boundary processing method designed herein to fuse, at the decision level, temporal sequence information with scene priori information. Experiments using public datasets and self-built industrial scene datasets show that due to the expansion of information sources, the quality of single-frame images has less impact on the recognition results, whereby the object recognition is greatly improved. It is presented herein as a widely applicable framework for the fusion of information under multiple classes. All the object recognition algorithms that output object class, location information and recognition confidence at the same time can be integrated into this information fusion framework to improve performance.展开更多
Max vision是比利时服装品牌,主要经营女装和童装。业主Jan是比利时人,因喜欢中国文化来到中国,并把家和办公室安在了宁波。本项目是在一栋新建别墅上改建办公。建筑共四层,且地下室只有1.9米高。设计带来的难度是如何在具有居住功能,...Max vision是比利时服装品牌,主要经营女装和童装。业主Jan是比利时人,因喜欢中国文化来到中国,并把家和办公室安在了宁波。本项目是在一栋新建别墅上改建办公。建筑共四层,且地下室只有1.9米高。设计带来的难度是如何在具有居住功能,开间跨度相对局限的建筑基础上解决日常办公的功能问题。展开更多
目前立体图像质量评价算法缺乏可靠的预测性能,主要表现在研究人类视觉系统时生物学理论薄弱,并且已有的浅层模型无法模拟出视觉信息复杂的处理过程。针对上述问题,提出一种基于交互式卷积神经网络的无参考立体图像质量评价算法。根据...目前立体图像质量评价算法缺乏可靠的预测性能,主要表现在研究人类视觉系统时生物学理论薄弱,并且已有的浅层模型无法模拟出视觉信息复杂的处理过程。针对上述问题,提出一种基于交互式卷积神经网络的无参考立体图像质量评价算法。根据初级视觉区域的双目视觉机制,融合左、右视图生成独眼特征图,并采用高斯差分算法提取左、右视图边缘信息,计算边缘求和以及差分特征图;搭建交互式卷积神经网络,整合特征图,实现深度特征学习和质量回归预测。在LIVE立体图像库上的Pearson线性相关系数(Pearson Linear Correlation Coefficient,PLCC)达到0.95以上,结果表明采用该算法能有效地解决失真立体图像质量评价问题。展开更多
基金funded by China State Forestry and Grassland Administration Project for Rescue and Captive Breeding of Endangered and Rare Wildlife(2018).
文摘Reintroduction is an important strategy to restore or re-establish wild populations of endangered species.Pre-release training is a necessary step to ensure postreintroduction survival.However,studies reported contradicting outcomes after pre-release training of juveniles and adults.This study used farmed and feral American mink(Neovison vison)to analyze the influence of captive breeding on the morphology,structure and efficiency of the two major hindlimb levers,the femur and tibia pivoted by hip and knee joints that are essential for locomotion.Results showed that captive breeding did not alter the sexual dimorphism of the two levers that are related to survival in the wild.Captive-bred mink showed slightly altered morphology of the femur and fundamental structure of the hindlimb levers that improved efficiency,but this resulted in reduction of performance related to foraging in both terrestrial and aquatic environments,especially for females.These findings suggest that reintroduction of mustelid as exampled by the mink here should focus on juveniles because the skeletal alterations associated with captive rearing were recorded only among adults and are irreversible in adulthood.In contrast,captive-reared juveniles showed no skeletal alterations and would be expected to recovery from any atrophy of the muscular system caused by captive rearing for shorter durations.Our results support the application of pre-release training of juveniles in enriched environments as a method for alleviating structural alteration of appendages and enhancing locomotion to increase survival probability in complex habitats.
文摘For some important object recognition applications such as intelligent robots and unmanned driving, images are collected on a consecutive basis and associated among themselves, besides, the scenes have steady prior features. Yet existing technologies do not take full advantage of this information. In order to take object recognition further than existing algorithms in the above application, an object recognition method that fuses temporal sequence with scene priori information is proposed. This method first employs YOLOv3 as the basic algorithm to recognize objects in single-frame images, then the DeepSort algorithm to establish association among potential objects recognized in images of different moments, and finally the confidence fusion method and temporal boundary processing method designed herein to fuse, at the decision level, temporal sequence information with scene priori information. Experiments using public datasets and self-built industrial scene datasets show that due to the expansion of information sources, the quality of single-frame images has less impact on the recognition results, whereby the object recognition is greatly improved. It is presented herein as a widely applicable framework for the fusion of information under multiple classes. All the object recognition algorithms that output object class, location information and recognition confidence at the same time can be integrated into this information fusion framework to improve performance.
文摘目前立体图像质量评价算法缺乏可靠的预测性能,主要表现在研究人类视觉系统时生物学理论薄弱,并且已有的浅层模型无法模拟出视觉信息复杂的处理过程。针对上述问题,提出一种基于交互式卷积神经网络的无参考立体图像质量评价算法。根据初级视觉区域的双目视觉机制,融合左、右视图生成独眼特征图,并采用高斯差分算法提取左、右视图边缘信息,计算边缘求和以及差分特征图;搭建交互式卷积神经网络,整合特征图,实现深度特征学习和质量回归预测。在LIVE立体图像库上的Pearson线性相关系数(Pearson Linear Correlation Coefficient,PLCC)达到0.95以上,结果表明采用该算法能有效地解决失真立体图像质量评价问题。
