Results 21 to 30 of about 1,094,036 (234)
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
Review of Deep Learning Applied to Occluded Object Detection [PDF]
Jisuanji kexue yu tansuo, 2022 Occluded object detection has long been a difficulty and hot topic in the field of computer vision. Based on convolutional neural network, the deep learning takes the object detection task as a classification and regression task to handle, and obtains ...
SUN Fangwei, LI Chengyang, XIE Yongqiang, LI Zhongbo, YANG Caidong, QI Jin
doaj +1 more source
3D Object Class Detection in the Wild [PDF]
, 2015 Object class detection has been a synonym for 2D bounding box localization for the longest time, fueled by the success of powerful statistical learning techniques, combined with robust image representations.
Gehler, Peter +4 more
core +1 more source
Remote Sensing, 2022 In high-resolution earth observation systems, object detection in high spatial resolution remote sensing images (HSRIs) is the key technology for automatic extraction, analysis and understanding of image information.
Zhipeng Dong +5 more
doaj +1 more source
DOTA: A Large-scale Dataset for Object Detection in Aerial Images [PDF]
, 2018 Object detection is an important and challenging problem in computer vision. Although the past decade has witnessed major advances in object detection in natural scenes, such successes have been slow to aerial imagery, not only because of the huge ...
Bai, Xiang +8 more
core +2 more sources
Video Object Detection Guided by Object Blur Evaluation
IEEE Access, 2020 In recent years, the excellent image-based object detection algorithms are transferred to the video object detection directly. These frame-by-frame processing methods are suboptimal owing to the degenerate object appearance such as motion blur, defocus ...
Yujie Wu +4 more
doaj +1 more source
RecFRCN: Few-Shot Object Detection With Recalibrated Faster R-CNN
IEEE Access, 2023 Currently, Faster R-CNN serves as the fundamental detection framework in the majority of few-shot object detection algorithms. However, due to limited samples per class, the Faster R-CNN’s classification branch faces limitations in capturing ...
Youyou Zhang, Tongwei Lu
doaj +1 more source
Illumination invariant stationary object detection [PDF]
, 2013 A real-time system for the detection and tracking of moving objects that becomes stationary in a restricted zone. A new pixel classification method based on the segmentation history image is used to identify stationary objects in the scene. These objects
Bhargav Mitra +7 more
core +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
Improving Small Object Proposals for Company Logo Detection [PDF]
, 2017 Many modern approaches for object detection are two-staged pipelines. The first stage identifies regions of interest which are then classified in the second stage.
Bell S. +6 more
core +2 more sources