An Improved New YOLOv7 Algorithm for Detecting Building Air Conditioner External Units from Street View Images [PDF]
Sensors, 2023 Street view images are emerging as new street-level sources of urban environmental information. Accurate detection and quantification of urban air conditioners is crucial for evaluating the resilience of urban residential areas to heat wave disasters and
Zhongmin Tian, Fei Yang, Donghong Qin
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Developing Sidewalk Inventory Data Using Street View Images [PDF]
Sensors, 2021 (1) Background: Public sidewalk GIS data are essential for smart city development. We developed an automated street-level sidewalk detection method with image-processing Google Street View data.
Bumjoon Kang, Sangwon Lee, Shengyuan Zou
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Integrating Aerial and Street View Images for Urban Land Use Classification
Remote Sensing, 2018 Urban land use is key to rational urban planning and management. Traditional land use classification methods rely heavily on domain experts, which is both expensive and inefficient.
Rui Cao +7 more
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Domain adaptation using transformer models for automated detection of exterior cladding materials in street view images [PDF]
Scientific ReportsRecent advances in deep learning have achieved impressive accuracy in various building analysis tasks using street view imagery). However, a major challenge lies in the large-scale, labeled datasets typically required—an obstacle driven by limited raw ...
Seunghyeon Wang
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Development of approach to an automated acquisition of static street view images using transformer architecture for analysis of Building characteristics [PDF]
Scientific ReportsStatic Street View Images (SSVIs) are widely used in urban studies to analyze building characteristics. Typically, camera parameters such as pitch and heading need precise adjustments to clearly capture these features. However, system errors during image
Seunghyeon Wang
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Parcel feature data derived from Google Street View images for urban land use classification in Brooklyn, New York Cityfor urban land use classification in Brooklyn, New York Cityretain--> [PDF]
Data in Brief, 2017 Google Street View (GSV) was used for urban land use classification, together with airborne light detection and ranging (LiDAR) data and high resolution orthoimagery, by a parcel-based method.
Weixing Zhang +5 more
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USE-SVI: A reproducible pipeline for sampling, acquiring, and stitching Street View imagery to support urban analyticsI have shared my data/code at [PDF]
MethodsXStreet-level imagery (SLI) is increasingly used in urban analytics for tasks like estimating greenery, conducting transport audits, and assessing facades.
Iuria Betco +2 more
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BuildingsStreet quality plays a crucial role in promoting urban development. There is still no consensus on how to quantify human street quality perception on a large scale or explore the relationship between street quality and street composition elements.
Yalun Lei +6 more
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Multi‐scale attention encoder for street‐to‐aerial image geo‐localization
CAAI Transactions on Intelligence Technology, 2023 The goal of street‐to‐aerial cross‐view image geo‐localization is to determine the location of the query street‐view image by retrieving the aerial‐view image from the same place.
Songlian Li +3 more
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Redai dili, 2023 Street vendors are an indispensable part of the urban social ecosystem, but due to a lack of comprehensive understanding, many cities have adopted simple eviction policies, resulting in the gradual marginalization and stigmatization of the street economy.
Liu Yuchen +4 more
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