Matches in SemOpenAlex for { <https://semopenalex.org/work/W4225638085> ?p ?o ?g. }
Showing items 1 to 61 of
61
with 100 items per page.
- W4225638085 abstract "Computer vision-based deep learning object detection algorithms have been developed sufficiently powerful to support the ability to recognize various objects. Although there are currently general datasets for object detection, there is still a lack of large-scale, open-source dataset for the construction industry, which limits the developments of object detection algorithms as they tend to be data-hungry. Therefore, this paper develops a new large-scale image dataset specifically collected and annotated for the construction site, called Site Object Detection dAtaset (SODA), which contains 15 kinds of object classes categorized by workers, materials, machines, and layout. Firstly, more than 20,000 images were collected from multiple construction sites in different site conditions, weather conditions, and construction phases, which covered different angles and perspectives. After careful screening and processing, 19,846 images including 286,201 objects were then obtained and annotated with labels in accordance with predefined categories. Statistical analysis shows that the developed dataset is advantageous in terms of diversity and volume. Further evaluation with two widely-adopted object detection algorithms based on deep learning (YOLO v3/ YOLO v4) also illustrates the feasibility of the dataset for typical construction scenarios, achieving a maximum mAP of 81.47%. In this manner, this research contributes a large-scale image dataset for the development of deep learning-based object detection methods in the construction industry and sets up a performance benchmark for further evaluation of corresponding algorithms in this area." @default.
- W4225638085 created "2022-05-05" @default.
- W4225638085 creator A5033655357 @default.
- W4225638085 creator A5052875226 @default.
- W4225638085 creator A5075553656 @default.
- W4225638085 creator A5081902178 @default.
- W4225638085 creator A5089178051 @default.
- W4225638085 date "2022-02-19" @default.
- W4225638085 modified "2023-09-26" @default.
- W4225638085 title "SODA: Site Object Detection dAtaset for Deep Learning in Construction" @default.
- W4225638085 doi "https://doi.org/10.48550/arxiv.2202.09554" @default.
- W4225638085 hasPublicationYear "2022" @default.
- W4225638085 type Work @default.
- W4225638085 citedByCount "0" @default.
- W4225638085 crossrefType "posted-content" @default.
- W4225638085 hasAuthorship W4225638085A5033655357 @default.
- W4225638085 hasAuthorship W4225638085A5052875226 @default.
- W4225638085 hasAuthorship W4225638085A5075553656 @default.
- W4225638085 hasAuthorship W4225638085A5081902178 @default.
- W4225638085 hasAuthorship W4225638085A5089178051 @default.
- W4225638085 hasBestOaLocation W42256380851 @default.
- W4225638085 hasConcept C108583219 @default.
- W4225638085 hasConcept C119857082 @default.
- W4225638085 hasConcept C124101348 @default.
- W4225638085 hasConcept C153180895 @default.
- W4225638085 hasConcept C154945302 @default.
- W4225638085 hasConcept C185798385 @default.
- W4225638085 hasConcept C205649164 @default.
- W4225638085 hasConcept C2776151529 @default.
- W4225638085 hasConcept C2778755073 @default.
- W4225638085 hasConcept C2781238097 @default.
- W4225638085 hasConcept C41008148 @default.
- W4225638085 hasConcept C58640448 @default.
- W4225638085 hasConceptScore W4225638085C108583219 @default.
- W4225638085 hasConceptScore W4225638085C119857082 @default.
- W4225638085 hasConceptScore W4225638085C124101348 @default.
- W4225638085 hasConceptScore W4225638085C153180895 @default.
- W4225638085 hasConceptScore W4225638085C154945302 @default.
- W4225638085 hasConceptScore W4225638085C185798385 @default.
- W4225638085 hasConceptScore W4225638085C205649164 @default.
- W4225638085 hasConceptScore W4225638085C2776151529 @default.
- W4225638085 hasConceptScore W4225638085C2778755073 @default.
- W4225638085 hasConceptScore W4225638085C2781238097 @default.
- W4225638085 hasConceptScore W4225638085C41008148 @default.
- W4225638085 hasConceptScore W4225638085C58640448 @default.
- W4225638085 hasLocation W42256380851 @default.
- W4225638085 hasOpenAccess W4225638085 @default.
- W4225638085 hasPrimaryLocation W42256380851 @default.
- W4225638085 hasRelatedWork W2610408157 @default.
- W4225638085 hasRelatedWork W2765476116 @default.
- W4225638085 hasRelatedWork W2769179720 @default.
- W4225638085 hasRelatedWork W2942557407 @default.
- W4225638085 hasRelatedWork W2946567716 @default.
- W4225638085 hasRelatedWork W3210378990 @default.
- W4225638085 hasRelatedWork W4214827935 @default.
- W4225638085 hasRelatedWork W4225308791 @default.
- W4225638085 hasRelatedWork W4281986673 @default.
- W4225638085 hasRelatedWork W4289884281 @default.
- W4225638085 isParatext "false" @default.
- W4225638085 isRetracted "false" @default.
- W4225638085 workType "article" @default.