White shark comparison reveals a slender body for the extinct megatooth shark, Otodus megalodon (Lamniformes: Otodontidae) - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Palaeontologia Electronica Année : 2024

White shark comparison reveals a slender body for the extinct megatooth shark, Otodus megalodon (Lamniformes: Otodontidae)

Gavin J.P. Naylor
John G. Maisey
  • Fonction : Auteur
Taketeru Tomita
  • Fonction : Auteur
Joshua K. Moyer
  • Fonction : Auteur
Timothy E. Higham
  • Fonction : Auteur
Hugo Bornatowski
  • Fonction : Auteur
Douglas J. Long
  • Fonction : Auteur
Victor J. Perez
  • Fonction : Auteur
Alberto Collareta
  • Fonction : Auteur
  • PersonId : 1138795
David J Ward
  • Fonction : Auteur
Romain Vullo
Kenshu Shimada
  • Fonction : Auteur correspondant

Résumé

In Advanced Driving Assistance Systems (ADAS), Automated Driving Systems (ADS), and Driver Assistance Systems (DAS), RGB camera sensors are extensively utilized for object detection, semantic segmentation, and object tracking. Despite their popularity due to low costs, RGB cameras exhibit weak robustness in complex environments, particularly underperforming in low-light conditions, which raises a significant concern. To address these challenges, multi-sensor fusion systems or specialized low-light cameras have been proposed, but their high costs render them unsuitable for widespread deployment. On the other hand, improvements in post-processing algorithms offer a more economical and effective solution. However, current research in low-light image enhancement still shows substantial gaps in detail enhancement on nighttime driving datasets and is characterized by high deployment costs, failing to achieve real-time inference and edge deployment. Therefore, this paper leverages the Swin Vision Transformer combined with a gamma transformation integrated U-Net for the decoupled enhancement of initial low-light inputs, proposing a deep learning enhancement network named Vehicle-based Efficient Low-light Image Enhancement (VELIE). VELIE achieves state-of-the-art performance on various driving datasets with a processing time of only 0.19 s, significantly enhancing high-dimensional environmental perception tasks in low-light conditions.

Domaines

Paléontologie
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Dates et versions

hal-04483958 , version 1 (29-02-2024)

Identifiants

Citer

Phillip C. Sternes, Patrick L. Jambura, Julia Tuertscher, Jurgen Kriwet, Mikael Siversson, et al.. White shark comparison reveals a slender body for the extinct megatooth shark, Otodus megalodon (Lamniformes: Otodontidae). Palaeontologia Electronica, 2024, Palaeontologia Electronica, ⟨10.26879/1345⟩. ⟨hal-04483958⟩
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