Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385482839> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W4385482839 abstract "This study attempted to construct a thermal dataset of human gait in diverse environments suitable for building and evaluating sophisticated deep learning models (e.g., vision transformers) for gait recognition. Gait is a behavioral biometric to identify a person and requires no cooperation from the person, making it suitable for security and surveillance applications. For security purposes, it is desirable to be able to recognize a person in darkness or other inadequate lighting conditions, in which thermal imagery is advantageous over visible light imagery. Despite the importance of such nighttime person identification, available thermal gait datasets captured in the dark are scarce. This study, therefore, collected a relatively large set of thermal gait data in both indoor and outdoor environments with several walking styles, e.g., walking normally, walking while carrying a bag, and walking fast. This dataset was utilized in multiple gait recognition tasks, such as gender classification and person verification, using legacy convolutional neural networks (CNNs) and modern vision transformers (ViTs). Experiments using this dataset revealed the effective training method for person ver-ification, the effectiveness of ViT on gait recognition, and the robustness of the models against the difference in walking styles; it suggests that the developed dataset enables various studies on gait recognition using state-of-the-art deep learning models." @default.
- W4385482839 created "2023-08-03" @default.
- W4385482839 creator A5020863121 @default.
- W4385482839 creator A5066618929 @default.
- W4385482839 creator A5087632404 @default.
- W4385482839 creator A5081345370 @default.
- W4385482839 date "2023-06-18" @default.
- W4385482839 modified "2023-09-23" @default.
- W4385482839 title "Thermal Gait Dataset for Deep Learning-Oriented Gait Recognition" @default.
- W4385482839 cites W1937803928 @default.
- W4385482839 cites W2050785999 @default.
- W4385482839 cites W2136504992 @default.
- W4385482839 cites W2308101195 @default.
- W4385482839 cites W2746562333 @default.
- W4385482839 cites W2807624910 @default.
- W4385482839 cites W2897874865 @default.
- W4385482839 cites W2966208575 @default.
- W4385482839 cites W3089166767 @default.
- W4385482839 cites W3107569347 @default.
- W4385482839 cites W4205268692 @default.
- W4385482839 cites W4206706211 @default.
- W4385482839 cites W4214612132 @default.
- W4385482839 cites W4284964780 @default.
- W4385482839 cites W4285290258 @default.
- W4385482839 cites W4292771416 @default.
- W4385482839 doi "https://doi.org/10.1109/ijcnn54540.2023.10191513" @default.
- W4385482839 hasPublicationYear "2023" @default.
- W4385482839 type Work @default.
- W4385482839 citedByCount "0" @default.
- W4385482839 crossrefType "proceedings-article" @default.
- W4385482839 hasAuthorship W4385482839A5020863121 @default.
- W4385482839 hasAuthorship W4385482839A5066618929 @default.
- W4385482839 hasAuthorship W4385482839A5081345370 @default.
- W4385482839 hasAuthorship W4385482839A5087632404 @default.
- W4385482839 hasConcept C104317684 @default.
- W4385482839 hasConcept C108583219 @default.
- W4385482839 hasConcept C119857082 @default.
- W4385482839 hasConcept C151800584 @default.
- W4385482839 hasConcept C154945302 @default.
- W4385482839 hasConcept C173906292 @default.
- W4385482839 hasConcept C184297639 @default.
- W4385482839 hasConcept C185592680 @default.
- W4385482839 hasConcept C31972630 @default.
- W4385482839 hasConcept C41008148 @default.
- W4385482839 hasConcept C55493867 @default.
- W4385482839 hasConcept C63479239 @default.
- W4385482839 hasConcept C71924100 @default.
- W4385482839 hasConcept C81363708 @default.
- W4385482839 hasConcept C99508421 @default.
- W4385482839 hasConceptScore W4385482839C104317684 @default.
- W4385482839 hasConceptScore W4385482839C108583219 @default.
- W4385482839 hasConceptScore W4385482839C119857082 @default.
- W4385482839 hasConceptScore W4385482839C151800584 @default.
- W4385482839 hasConceptScore W4385482839C154945302 @default.
- W4385482839 hasConceptScore W4385482839C173906292 @default.
- W4385482839 hasConceptScore W4385482839C184297639 @default.
- W4385482839 hasConceptScore W4385482839C185592680 @default.
- W4385482839 hasConceptScore W4385482839C31972630 @default.
- W4385482839 hasConceptScore W4385482839C41008148 @default.
- W4385482839 hasConceptScore W4385482839C55493867 @default.
- W4385482839 hasConceptScore W4385482839C63479239 @default.
- W4385482839 hasConceptScore W4385482839C71924100 @default.
- W4385482839 hasConceptScore W4385482839C81363708 @default.
- W4385482839 hasConceptScore W4385482839C99508421 @default.
- W4385482839 hasLocation W43854828391 @default.
- W4385482839 hasOpenAccess W4385482839 @default.
- W4385482839 hasPrimaryLocation W43854828391 @default.
- W4385482839 hasRelatedWork W2035976912 @default.
- W4385482839 hasRelatedWork W2541791370 @default.
- W4385482839 hasRelatedWork W2731899572 @default.
- W4385482839 hasRelatedWork W2999805992 @default.
- W4385482839 hasRelatedWork W3116150086 @default.
- W4385482839 hasRelatedWork W3133861977 @default.
- W4385482839 hasRelatedWork W4200173597 @default.
- W4385482839 hasRelatedWork W4312417841 @default.
- W4385482839 hasRelatedWork W4321369474 @default.
- W4385482839 hasRelatedWork W4380075502 @default.
- W4385482839 isParatext "false" @default.
- W4385482839 isRetracted "false" @default.
- W4385482839 workType "article" @default.