Results 51 to 60 of about 3,676,418 (303)
Remote SensingSelf-supervised monocular depth estimation methods have become the focus of research since ground truth data are not required. Current single-image-based works only leverage appearance-based features, thus achieving a limited performance.
Xiaotong Guo +5 more
doaj +1 more source
Artificial molecular machines and motors—Design and control of nanoscale motion
FEBS Letters, EarlyView.Molecules are constantly moving because of thermal fluctuations, but random motion alone cannot be exploited to perform directional tasks. Artificial molecular machines use chemical, electrical, or light energy to bias this motion. Molecular shuttles, rotary motors, and supramolecular pumps illustrate how nanoscale movement can be controlled and ...
Leonardo Andreoni, Alberto Credi
wiley +1 more source
Depth-Relative Self Attention for Monocular Depth Estimation
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023 Monocular depth estimation is very challenging because clues to the exact depth are incomplete in a single RGB image. To overcome the limitation, deep neural networks rely on various visual hints such as size, shade, and texture extracted from RGB information. However, we observe that if such hints are overly exploited, the network can be biased on RGB
Kyuhong Shim +3 more
openaire +2 more sources
The role of miR‐335‐5p in the redifferentiation of BRAF p.V600E thyroid cancers
Molecular Oncology, EarlyView.The BRAF p.V600E mutation promotes thyroid cancer dedifferentiation and radioiodine resistance. Using a network approach, we identified miR‐335‐5p as a key regulator of BRAF‐mutated thyroid tumors. Restoring miR‐335‐5p increased thyroid‐specific gene expression and iodine uptake in cells and organoids.
Valeria Pecce +11 more
wiley +1 more source
Depth Map Estimation for Free-Viewpoint Television and Virtual Navigation
IEEE Access, 2020 The paper presents a new method of depth estimation, dedicated for free-viewpoint television (FTV) and virtual navigation (VN). In this method, multiple arbitrarily positioned input views are simultaneously used to produce depth maps characterized by ...
Dawid Mieloch +2 more
doaj +1 more source
Depth Prompting for Sensor-Agnostic Depth Estimation
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Accepted at CVPR ...
Jin-Hwi Park +3 more
openaire +3 more sources
Molecular Oncology, EarlyView.In this explorative study, the abundance of circular RNA molecules in bone marrow stem cells was found to be elevated in patients with high‐risk myelodysplastic neoplasms, and to be associated with an increased risk of progression to acute myeloid leukemia.
Eileen Wedge +17 more
wiley +1 more source
Molecular Oncology, EarlyView.Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur +11 more
wiley +1 more source
Depth Acquisition from Digital Images [PDF]
, 2011 Introduction: Depth acquisition from digital images captured with a conventional camera, by analysing focus/defocus cues which are related to depth via an optical model of the camera, is a popular approach to depth-mapping a 3D scene.
WILLIAMS, DAVID,NICHOLAS
core
Optimising Aperture Shapes for Depth Estimation
, 2013 The finite depth of field of a real camera can be used to estimate the depth structure of a scene. While the distance of an object from the plane in focus determines the defocus blur size, the shape of the aperture determines the shape of the blur.
Favaro, Paolo, Sellent, Anita
core +1 more source