Zobrazeno 1 - 10
of 114
pro vyhledávání: '"Linjun Lu"'
Publikováno v:
Land, Vol 13, Iss 8, p 1233 (2024)
Numerous researchers have endeavored to amalgamate critical transit-oriented development (TOD) indicators, such as development density, walkability, and diversity, into a single TOD index to assess TOD performance. However, implementing TOD in megaci
Externí odkaz:
https://doaj.org/article/54868d2a78b241d49ff5c4fdee787eac
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract Salient object detection is vital for non-specific class subject segmentation in computer vision applications. However, accurately segmenting foreground subjects with complex backgrounds and intricate boundaries remains a challenge for exist
Externí odkaz:
https://doaj.org/article/325427c25ae74621b5ca80625111dacd
Publikováno v:
Journal of Advanced Transportation, Vol 2024 (2024)
Transit-oriented development (TOD) strategies on subway stations have been implemented in many high-density cities globally to enhance public transportation system efficiency and promote public transportation mobility. Focusing on the developments of
Externí odkaz:
https://doaj.org/article/eb662c606e5c4c2680849f0ca7e14ba6
Publikováno v:
Journal of Advanced Transportation, Vol 2024 (2024)
One of the most important goals of cooperative driving is to control connected automated vehicles (CAVs) passing through conflict areas safely and efficiently without traffic signals. As a typical application scenario, allocating right-of-way reasona
Externí odkaz:
https://doaj.org/article/8b3a169374e94f8f9d5970ac5d0c5edb
Spatial Downscaling of ESA CCI Soil Moisture Data Based on Deep Learning with an Attention Mechanism
Publikováno v:
Remote Sensing, Vol 16, Iss 8, p 1394 (2024)
Soil moisture (SM) is a critical variable affecting ecosystem carbon and water cycles and their feedback to climate change. In this study, we proposed a convolutional neural network (CNN) model embedded with a residual block and attention module, nam
Externí odkaz:
https://doaj.org/article/c538bbfdd8cc47c28a89d90476b97a5a
Publikováno v:
IEEE Access, Vol 11, Pp 27217-27225 (2023)
Deep neural networks (DNNs) are vulnerable to adversarial attacks. In particular, object detectors may be attacked by applying a particular adversarial patch to the image. However, because the patch will lose information during the shrinking process,
Externí odkaz:
https://doaj.org/article/bd28c608987a451ba422395c34301101
Publikováno v:
Remote Sensing, Vol 15, Iss 19, p 4831 (2023)
Partitioning evapotranspiration (ET) into vegetation transpiration (T) and soil evaporation (E) is challenging, but it is key to improving the understanding of plant water use and changes in terrestrial ecosystems. Considering that the transpiration
Externí odkaz:
https://doaj.org/article/3b5ddf6e52b5409a8e0f2da0fae6023d
Publikováno v:
Journal of Advanced Transportation, Vol 2023 (2023)
Parking lots have many complex structures, diverse functions, and plentiful elements. The frequent flow of vehicles with narrow and dim spaces increases the probability of various traffic accidents. Due to the low severity and lack of relevant data,
Externí odkaz:
https://doaj.org/article/86c69a03bc1646ec81bfc7ba3a5f3b72
Publikováno v:
Journal of Advanced Transportation, Vol 2022 (2022)
Malignant traffic accidents are typical devastating events suffered by the urban road network. They cause severe functional loss when loading on the urban road network is high, exerting a significant impact on the operation of the city. The resilienc
Externí odkaz:
https://doaj.org/article/9405b99f70504577b4e0bdec15bff1d5
Publikováno v:
Journal of Advanced Transportation, Vol 2020 (2020)
Adverse weather condition is one of the inducements that lead to supply uncertainty of an urban transportation system, while travelers’ multiple route choice criteria are the nonignorable reason resulting in demand uncertainty. This paper proposes
Externí odkaz:
https://doaj.org/article/e3e5292fc95e490bb6ecc20a5e40bd61