Results 21 to 30 of about 4,616,264 (348)
An in-depth map of polyadenylation sites in cancer. [PDF]
Nucleic Acids Res, 2012 We present a comprehensive map of over 1 million polyadenylation sites and quantify their usage in major cancers and tumor cell lines using direct RNA sequencing. We built the Expression and Polyadenylation Database to enable the visualization of the polyadenylation maps in various cancers and to facilitate the discovery of novel genes and gene ...
Lin Y +10 more
europepmc +7 more sources
Constraining Depth Map Geometry for Multi-View Stereo: A Dual-Depth Approach with Saddle-shaped Depth Cells [PDF]
IEEE International Conference on Computer Vision, 2023 Learning-based multi-view stereo (MVS) methods deal with predicting accurate depth maps to achieve an accurate and complete 3D representation. Despite the excellent performance, existing methods ignore the fact that a suitable depth geometry is also ...
Xinyi Ye +5 more
semanticscholar +1 more source
Depth Estimation Based on Scene Object Attention and Depth Map Fusion [PDF]
Jisuanji gongcheng, 2023 The existing monocular depth estimation algorithm mainly obtains stereo information from a single image.This approach leads to blurred details of adjacent depth edges and apparent missing objects.A monocular depth estimation algorithm based on scene ...
WEN Jing, YANG Jie
doaj +1 more source
Discrete Cosine Transform Network for Guided Depth Map Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2021 Guided depth super-resolution (GDSR) is an essential topic in multi-modal image processing, which reconstructs high-resolution (HR) depth maps from low-resolution ones collected with suboptimal conditions with the help of HR RGB images of the same scene.
Zixiang Zhao +4 more
semanticscholar +1 more source
BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation [PDF]
ACM Multimedia, 2021 Depth map super-resolution is a task with high practical application requirements in the industry. Existing color-guided depth map super-resolution methods usually necessitate an extra branch to extract high-frequency detail information from RGB image to
Q. Tang +6 more
semanticscholar +1 more source
Learning Occlusion-aware Coarse-to-Fine Depth Map for Self-supervised Monocular Depth Estimation [PDF]
ACM Multimedia, 2022 Self-supervised monocular depth estimation, aiming to learn scene depths from single images in a self-supervised manner, has received much attention recently.
Zhengming Zhou, Qiulei Dong
semanticscholar +1 more source
Monocular Depth Estimation Based on Multi-Scale Depth Map Fusion
IEEE Access, 2021 Monocular depth estimation is a basic task in machine vision. In recent years, the performance of monocular depth estimation has been greatly improved. However, most depth estimation networks are based on a very deep network to extract features that lead
Xin Yang +4 more
doaj +1 more source
Depth Map Super-Resolution Using Guided Deformable Convolution
IEEE Access, 2021 Depth maps acquired by low-cost sensors have low spatial resolution, which restricts their usefulness in many image processing and computer vision tasks.
Joon-Yeon Kim +4 more
doaj +1 more source
Depth Map Super-Resolution via Cascaded Transformers Guidance
Frontiers in Signal Processing, 2022 Depth information captured by affordable depth sensors is characterized by low spatial resolution, which limits potential applications. Several methods have recently been proposed for guided super-resolution of depth maps using convolutional neural ...
Ido Ariav, Israel Cohen
doaj +1 more source
RoutedFusion: Learning Real-Time Depth Map Fusion [PDF]
Computer Vision and Pattern Recognition, 2020 The efficient fusion of depth maps is a key part of most state-of-the-art 3D reconstruction methods. Besides requiring high accuracy, these depth fusion methods need to be scalable and real-time capable.
Silvan Weder +3 more
semanticscholar +1 more source