Semantic segmentation of driving scene images is crucial for autonomous driving.While deep learning technology has significantly improved daytime image semantic segmentation,nighttime images pose challenges due to fac...Semantic segmentation of driving scene images is crucial for autonomous driving.While deep learning technology has significantly improved daytime image semantic segmentation,nighttime images pose challenges due to factors like poor lighting and overexposure,making it difficult to recognize small objects.To address this,we propose an Image Adaptive Enhancement(IAEN)module comprising a parameter predictor(Edip),multiple image processing filters(Mdif),and a Detail Processing Module(DPM).Edip combines image processing filters to predict parameters like exposure and hue,optimizing image quality.We adopt a novel image encoder to enhance parameter prediction accuracy by enabling Edip to handle features at different scales.DPM strengthens overlooked image details,extending the IAEN module’s functionality.After the segmentation network,we integrate a Depth Guided Filter(DGF)to refine segmentation outputs.The entire network is trained end-to-end,with segmentation results guiding parameter prediction optimization,promoting self-learning and network improvement.This lightweight and efficient network architecture is particularly suitable for addressing challenges in nighttime image segmentation.Extensive experiments validate significant performance improvements of our approach on the ACDC-night and Nightcity datasets.展开更多
Urban night tourism is a new form of urban tourism development and an important driving force for the prosperity of urban night economy.As the most prestigious business card among many night tour projects in Guangzhou...Urban night tourism is a new form of urban tourism development and an important driving force for the prosperity of urban night economy.As the most prestigious business card among many night tour projects in Guangzhou,the Pearl River water night tour has contributed to the development of Guangzhou s night economy,which cannot be underestimated.However,in the process of rapid development,there are also problems such as diversified operators,insufficient integration of intangible cultural elements,excessive commercial attributes,issues of tourism facilities and service facilities.Under the new stage of integrated development of culture and tourism,how to use mutual promotion of culture and tourism in the Pearl River night tour to seek innovative paths for high-quality development in the future is the main problem expected to be solved in this paper.Therefore,based on the perspective of culture and tourism integration,this paper analyzes the general situation and development status of the Pearl River night tour,and proposes five development strategies:the overall planning of culture and tourism integration,the deep integration of intangible cultural elements,the balance of commercial attributes and tourism attributes,the high integration of culture,business,tourism and education,and the creation of tourism atmosphere,in order to provide inspiration for the healthy,orderly and high-quality development of the Pearl River night tour.展开更多
LED lights have been widely used in urban night space lighting in recent years as they are small,energy-saving,and efficient.This article explores the use of LEDs in bridge night space lighting and their application s...LED lights have been widely used in urban night space lighting in recent years as they are small,energy-saving,and efficient.This article explores the use of LEDs in bridge night space lighting and their application strategies.The aim is to offer valuable insights and references for urban planners and bridge lighting designers in China.By advancing the application of LED technology in bridge night lighting,the goal is to enhance the city’s nighttime ambiance,making the bridge an iconic landmark and a defining feature of the city.展开更多
Night lighting has been shown to affect wild animals.To date,the effects of night lighting on the metabolic homeostasis of birds that spend short time in urban environments remain unclear.Using model bird species Zebr...Night lighting has been shown to affect wild animals.To date,the effects of night lighting on the metabolic homeostasis of birds that spend short time in urban environments remain unclear.Using model bird species Zebra Finch(Taeniopygia guttata),we investigated the effects of short-term night lighting on liver transcriptome,blood glucose,triglyceride,and thyroxine(T4 and T3)levels in birds exposed to two different night lighting duration periods(three days and six days).After three days of night lighting exposure,the expression of genes involved in fat synthesis in the liver was upregulated while the expression of genes involved in fatty acid oxidation and triglyceride decomposition was downregulated.There was also a reduction in blood triglyceride,glucose,and T3 concentrations.However,after six days of night lighting,the expression of genes associated with fatty acid decomposition and hyperglycemia in the liver was upregulated,while the expression of genes involved in fat synthesis was downregulated.Simultaneously,blood glucose levels and T3 concentration increased.These findings indicate that short-term exposure to night lighting can disrupt the lipid and glucose metabolism of small passerine birds,and longer stopovers in urban area with intense night lighting may cause birds to consume more lipid energy.展开更多
Night tourism often involves a large number of lighting facilities,which consume a large amount of energy.Therefore,one of the unique low energy consumption natural ecological tourism activities—firefly night tour ha...Night tourism often involves a large number of lighting facilities,which consume a large amount of energy.Therefore,one of the unique low energy consumption natural ecological tourism activities—firefly night tour has attracted attention and become an important breakthrough point for night tourism in tourist destinations.In this paper,Guangzhou firefly night tour project is taken as the research object.Based on the comprehensive economic,environmental,and socio-cultural benefits brought by the development of firefly night tour,the resources distribution,current development status,and existing problems of firefly night tour in Guangzhou are analyzed,and its high-quality development paths are proposed from three levels:government,industry,and tourist.The aim is to explore a new model for the economic development of Guangzhou night tour,boosting the transformation and upgrading of the night tourism economy,while also providing reference ideas and value for the development of night tourism economy in other tourist destinations.展开更多
According to data from ii-Media Research,China’s night economy has grown rapidly since 2016.By the end of 2020,the scale of China’s night economy had exceeded RMB 30 trillion,an increase of 5.0%over the same period ...According to data from ii-Media Research,China’s night economy has grown rapidly since 2016.By the end of 2020,the scale of China’s night economy had exceeded RMB 30 trillion,an increase of 5.0%over the same period of last year,and it is expected to exceed RMB 48 trillion in 2023.According to the latest survey data of the Ocean Engine City Institute in 2023,more than 60%of respondents will go out for activities or consumption at night,among which citizens in high-speed cities have a higher preference for going out at night because of the relatively perfect urban infrastructure.展开更多
The visible-light imaging system used in military equipment is often subjected to severe weather conditions, such as fog, haze, and smoke, under complex lighting conditions at night that significantly degrade the acqu...The visible-light imaging system used in military equipment is often subjected to severe weather conditions, such as fog, haze, and smoke, under complex lighting conditions at night that significantly degrade the acquired images. Currently available image defogging methods are mostly suitable for environments with natural light in the daytime, but the clarity of images captured under complex lighting conditions and spatial changes in the presence of fog at night is not satisfactory. This study proposes an algorithm to remove night fog from single images based on an analysis of the statistical characteristics of images in scenes involving night fog. Color channel transfer is designed to compensate for the high attenuation channel of foggy images acquired at night. The distribution of transmittance is estimated by the deep convolutional network DehazeNet, and the spatial variation of atmospheric light is estimated in a point-by-point manner according to the maximum reflection prior to recover the clear image. The results of experiments show that the proposed method can compensate for the high attenuation channel of foggy images at night, remove the effect of glow from a multi-color and non-uniform ambient source of light, and improve the adaptability and visual effect of the removal of night fog from images compared with the conventional method.展开更多
In the UK,Bonfire Night or Guy Fawkes Night is celebrated on 5 November and the night skies are filled with colour.It’s a special day in honour of a historic event.
Improved picture quality is critical to the effectiveness of object recog-nition and tracking.The consistency of those photos is impacted by night-video systems because the contrast between high-profile items and diffe...Improved picture quality is critical to the effectiveness of object recog-nition and tracking.The consistency of those photos is impacted by night-video systems because the contrast between high-profile items and different atmospheric conditions,such as mist,fog,dust etc.The pictures then shift in intensity,colour,polarity and consistency.A general challenge for computer vision analyses lies in the horrid appearance of night images in arbitrary illumination and ambient envir-onments.In recent years,target recognition techniques focused on deep learning and machine learning have become standard algorithms for object detection with the exponential growth of computer performance capabilities.However,the iden-tification of objects in the night world also poses further problems because of the distorted backdrop and dim light.The Correlation aware LSTM based YOLO(You Look Only Once)classifier method for exact object recognition and deter-mining its properties under night vision was a major inspiration for this work.In order to create virtual target sets similar to daily environments,we employ night images as inputs;and to obtain high enhanced image using histogram based enhancement and iterative wienerfilter for removing the noise in the image.The process of the feature extraction and feature selection was done for electing the potential features using the Adaptive internal linear embedding(AILE)and uplift linear discriminant analysis(ULDA).The region of interest mask can be segmen-ted using the Recurrent-Phase Level set Segmentation.Finally,we use deep con-volution feature fusion and region of interest pooling to integrate the presently extremely sophisticated quicker Long short term memory based(LSTM)with YOLO method for object tracking system.A range of experimentalfindings demonstrate that our technique achieves high average accuracy with a precision of 99.7%for object detection of SSAN datasets that is considerably more than that of the other standard object detection mechanism.Our approach may therefore satisfy the true demands of night scene target detection applications.We very much believe that our method will help future research.展开更多
基金This work is supported in part by The National Natural Science Foundation of China(Grant Number 61971078),which provided domain expertise and computational power that greatly assisted the activityThis work was financially supported by Chongqing Municipal Education Commission Grants for-Major Science and Technology Project(Grant Number gzlcx20243175).
文摘Semantic segmentation of driving scene images is crucial for autonomous driving.While deep learning technology has significantly improved daytime image semantic segmentation,nighttime images pose challenges due to factors like poor lighting and overexposure,making it difficult to recognize small objects.To address this,we propose an Image Adaptive Enhancement(IAEN)module comprising a parameter predictor(Edip),multiple image processing filters(Mdif),and a Detail Processing Module(DPM).Edip combines image processing filters to predict parameters like exposure and hue,optimizing image quality.We adopt a novel image encoder to enhance parameter prediction accuracy by enabling Edip to handle features at different scales.DPM strengthens overlooked image details,extending the IAEN module’s functionality.After the segmentation network,we integrate a Depth Guided Filter(DGF)to refine segmentation outputs.The entire network is trained end-to-end,with segmentation results guiding parameter prediction optimization,promoting self-learning and network improvement.This lightweight and efficient network architecture is particularly suitable for addressing challenges in nighttime image segmentation.Extensive experiments validate significant performance improvements of our approach on the ACDC-night and Nightcity datasets.
基金the"14 th Five-year"Plan Project for the Development of Philosophy and Social Sciences of Guangzhou(2023GZGJ83)the Guangdong Ploytechnic of Industry and Commerce Project(2023-SKJ-20).
文摘Urban night tourism is a new form of urban tourism development and an important driving force for the prosperity of urban night economy.As the most prestigious business card among many night tour projects in Guangzhou,the Pearl River water night tour has contributed to the development of Guangzhou s night economy,which cannot be underestimated.However,in the process of rapid development,there are also problems such as diversified operators,insufficient integration of intangible cultural elements,excessive commercial attributes,issues of tourism facilities and service facilities.Under the new stage of integrated development of culture and tourism,how to use mutual promotion of culture and tourism in the Pearl River night tour to seek innovative paths for high-quality development in the future is the main problem expected to be solved in this paper.Therefore,based on the perspective of culture and tourism integration,this paper analyzes the general situation and development status of the Pearl River night tour,and proposes five development strategies:the overall planning of culture and tourism integration,the deep integration of intangible cultural elements,the balance of commercial attributes and tourism attributes,the high integration of culture,business,tourism and education,and the creation of tourism atmosphere,in order to provide inspiration for the healthy,orderly and high-quality development of the Pearl River night tour.
文摘LED lights have been widely used in urban night space lighting in recent years as they are small,energy-saving,and efficient.This article explores the use of LEDs in bridge night space lighting and their application strategies.The aim is to offer valuable insights and references for urban planners and bridge lighting designers in China.By advancing the application of LED technology in bridge night lighting,the goal is to enhance the city’s nighttime ambiance,making the bridge an iconic landmark and a defining feature of the city.
基金supported by grants from Key laboratory of Ecology and Environment in Minority Area,National Ethnic Affairs Commission(KLEEMA202207)the Graduate Research and Practice Projects of Minzu University of China(BZKY2022042).
文摘Night lighting has been shown to affect wild animals.To date,the effects of night lighting on the metabolic homeostasis of birds that spend short time in urban environments remain unclear.Using model bird species Zebra Finch(Taeniopygia guttata),we investigated the effects of short-term night lighting on liver transcriptome,blood glucose,triglyceride,and thyroxine(T4 and T3)levels in birds exposed to two different night lighting duration periods(three days and six days).After three days of night lighting exposure,the expression of genes involved in fat synthesis in the liver was upregulated while the expression of genes involved in fatty acid oxidation and triglyceride decomposition was downregulated.There was also a reduction in blood triglyceride,glucose,and T3 concentrations.However,after six days of night lighting,the expression of genes associated with fatty acid decomposition and hyperglycemia in the liver was upregulated,while the expression of genes involved in fat synthesis was downregulated.Simultaneously,blood glucose levels and T3 concentration increased.These findings indicate that short-term exposure to night lighting can disrupt the lipid and glucose metabolism of small passerine birds,and longer stopovers in urban area with intense night lighting may cause birds to consume more lipid energy.
基金the 14th Five-year Plan Project for the Development of Philosophy and Social Sciences of Guangzhou(2023GZGJ83)the 2021 General University Key Scientific Research Project of Department of Education of Guangdong Province(2021ZDZX4104)+1 种基金Project of Guangdong Provincial Department of Education(2021GDJG600,2021ZQXY45)the Guangdong Ploytechnic of Industry and Commerce Project(2023-SKJ-20).
文摘Night tourism often involves a large number of lighting facilities,which consume a large amount of energy.Therefore,one of the unique low energy consumption natural ecological tourism activities—firefly night tour has attracted attention and become an important breakthrough point for night tourism in tourist destinations.In this paper,Guangzhou firefly night tour project is taken as the research object.Based on the comprehensive economic,environmental,and socio-cultural benefits brought by the development of firefly night tour,the resources distribution,current development status,and existing problems of firefly night tour in Guangzhou are analyzed,and its high-quality development paths are proposed from three levels:government,industry,and tourist.The aim is to explore a new model for the economic development of Guangzhou night tour,boosting the transformation and upgrading of the night tourism economy,while also providing reference ideas and value for the development of night tourism economy in other tourist destinations.
文摘According to data from ii-Media Research,China’s night economy has grown rapidly since 2016.By the end of 2020,the scale of China’s night economy had exceeded RMB 30 trillion,an increase of 5.0%over the same period of last year,and it is expected to exceed RMB 48 trillion in 2023.According to the latest survey data of the Ocean Engine City Institute in 2023,more than 60%of respondents will go out for activities or consumption at night,among which citizens in high-speed cities have a higher preference for going out at night because of the relatively perfect urban infrastructure.
基金supported by a grant from the Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology (Grant No. GZZKFJJ2020004)the National Natural Science Foundation of China (Grant Nos. 61875013 and 61827814)the Natural Science Foundation of Beijing Municipality (Grant No. Z190018)。
文摘The visible-light imaging system used in military equipment is often subjected to severe weather conditions, such as fog, haze, and smoke, under complex lighting conditions at night that significantly degrade the acquired images. Currently available image defogging methods are mostly suitable for environments with natural light in the daytime, but the clarity of images captured under complex lighting conditions and spatial changes in the presence of fog at night is not satisfactory. This study proposes an algorithm to remove night fog from single images based on an analysis of the statistical characteristics of images in scenes involving night fog. Color channel transfer is designed to compensate for the high attenuation channel of foggy images acquired at night. The distribution of transmittance is estimated by the deep convolutional network DehazeNet, and the spatial variation of atmospheric light is estimated in a point-by-point manner according to the maximum reflection prior to recover the clear image. The results of experiments show that the proposed method can compensate for the high attenuation channel of foggy images at night, remove the effect of glow from a multi-color and non-uniform ambient source of light, and improve the adaptability and visual effect of the removal of night fog from images compared with the conventional method.
文摘In the UK,Bonfire Night or Guy Fawkes Night is celebrated on 5 November and the night skies are filled with colour.It’s a special day in honour of a historic event.
文摘Improved picture quality is critical to the effectiveness of object recog-nition and tracking.The consistency of those photos is impacted by night-video systems because the contrast between high-profile items and different atmospheric conditions,such as mist,fog,dust etc.The pictures then shift in intensity,colour,polarity and consistency.A general challenge for computer vision analyses lies in the horrid appearance of night images in arbitrary illumination and ambient envir-onments.In recent years,target recognition techniques focused on deep learning and machine learning have become standard algorithms for object detection with the exponential growth of computer performance capabilities.However,the iden-tification of objects in the night world also poses further problems because of the distorted backdrop and dim light.The Correlation aware LSTM based YOLO(You Look Only Once)classifier method for exact object recognition and deter-mining its properties under night vision was a major inspiration for this work.In order to create virtual target sets similar to daily environments,we employ night images as inputs;and to obtain high enhanced image using histogram based enhancement and iterative wienerfilter for removing the noise in the image.The process of the feature extraction and feature selection was done for electing the potential features using the Adaptive internal linear embedding(AILE)and uplift linear discriminant analysis(ULDA).The region of interest mask can be segmen-ted using the Recurrent-Phase Level set Segmentation.Finally,we use deep con-volution feature fusion and region of interest pooling to integrate the presently extremely sophisticated quicker Long short term memory based(LSTM)with YOLO method for object tracking system.A range of experimentalfindings demonstrate that our technique achieves high average accuracy with a precision of 99.7%for object detection of SSAN datasets that is considerably more than that of the other standard object detection mechanism.Our approach may therefore satisfy the true demands of night scene target detection applications.We very much believe that our method will help future research.