Results 31 to 40 of about 7,363,707 (395)
The Role of CaMKII Overexpression and Oxidation in Atrial Fibrillation—A Simulation Study
Frontiers in Physiology, 2020 This simulation study aims to investigate how the Calcium/calmodulin-dependent protein kinase II (CaMKII) overexpression and oxidation would influence the cardiac electrophysiological behavior and its arrhythmogenic mechanism in atria. A new-built CaMKII
Wei Wang +8 more
doaj +1 more source
Detect-and-describe: Joint learning framework for detection and description of objects [PDF]
, 2022 Traditional object detection answers two questions; "what" (what the object is?) and "where" (where the object is?). "what" part of the object detection can be fine-grained further i.e. "what type", "what shape" and "what material" etc. This results in the shifting of the object detection tasks to the object description paradigm.
arxiv +1 more source
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation [PDF]
2014 IEEE Conference on Computer Vision and Pattern Recognition, 2013 Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. The best-performing methods are complex ensemble systems that typically combine multiple low-level image features with high-level context.
Ross B. Girshick +3 more
semanticscholar +1 more source
BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection [PDF]
AAAI Conference on Artificial Intelligence, 2022 In this research, we propose a new 3D object detector with a trustworthy depth estimation, dubbed BEVDepth, for camera-based Bird's-Eye-View~(BEV) 3D object detection.
Yinhao Li +7 more
semanticscholar +1 more source
A Novel Multi-Scale Transformer for Object Detection in Aerial Scenes
Drones, 2022 Deep learning has promoted the research of object detection in aerial scenes. However, most of the existing networks are limited by the large-scale variation of objects and the confusion of category features.
Guanlin Lu +5 more
doaj +1 more source
Progressive Object Transfer Detection [PDF]
IEEE Transactions on Image Processing, 2020 Recent development of object detection mainly depends on deep learning with large-scale benchmarks. However, collecting such fully-annotated data is often difficult or expensive for real-world applications, which restricts the power of deep neural networks in practice.
Hao Chen +4 more
openaire +5 more sources
Object Detection With Deep Learning: A Review [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2018 Due to object detection’s close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable architectures.
Zhong-Qiu Zhao +3 more
semanticscholar +1 more source
Collision Detection for Deformable Objects [PDF]
Computer Graphics Forum, 2005 AbstractInteractive environments for dynamically deforming objects play an important role in surgery simulation and entertainment technology. These environments require fast deformable models and very efficient collision handling techniques. While collision detection for rigid bodies is well investigated, collision detection for deformable objects ...
Teschner, Matthias +10 more
openaire +9 more sources
CenterNet: Keypoint Triplets for Object Detection [PDF]
IEEE International Conference on Computer Vision, 2019 In object detection, keypoint-based approaches often experience the drawback of a large number of incorrect object bounding boxes, arguably due to the lack of an additional assessment inside cropped regions. This paper presents an efficient solution that
Kaiwen Duan +5 more
semanticscholar +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 RGB–infrared object detection in remote-sensing images is crucial for achieving around-clock surveillance of unmanned aerial vehicles.
Jin Xie +4 more
doaj +1 more source