Results 31 to 40 of about 832,071 (273)
DroneNet: Rescue Drone-View Object Detection
Drones, 2023 Recently, the research on drone-view object detection (DOD) has predominantly centered on efficiently identifying objects through cropping high-resolution images. However, it has overlooked the distinctive challenges posed by scale imbalance and a higher
Xiandong Wang +7 more
doaj +1 more source
Challenges in video based object detection in maritime scenario using computer vision [PDF]
, 2016 This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging ...
Prasad, D. K. +5 more
core +2 more sources
On Pairwise Costs for Network Flow Multi-Object Tracking [PDF]
, 2015 Multi-object tracking has been recently approached with the min-cost network flow optimization techniques. Such methods simultaneously resolve multiple object tracks in a video and enable modeling of dependencies among tracks.
Chari, Visesh +3 more
core +1 more source
Small Object Detection using Deep Learning
, 2022 Now a days, UAVs such as drones are greatly used for various purposes like that of capturing and target detection from ariel imagery etc. Easy access of these small ariel vehicles to public can cause serious security threats. For instance, critical places may be monitored by spies blended in public using drones.
Ajaz, Aleena +3 more
openaire +2 more sources
Deep learning-based small object detection: A survey
Mathematical Biosciences and Engineering, 2023 <abstract> <p>Small object detection (SOD) is significant for many real-world applications, including criminal investigation, autonomous driving and remote sensing images. SOD has been one of the most challenging tasks in computer vision due to its low resolution and noise representation.
Qihan Feng, Xinzheng Xu, Zhixiao Wang
openaire +3 more sources
Perceptual Generative Adversarial Networks for Small Object Detection
, 2017 Detecting small objects is notoriously challenging due to their low resolution and noisy representation. Existing object detection pipelines usually detect small objects through learning representations of all the objects at multiple scales. However, the
Feng, Jiashi +5 more
core +1 more source
, 2020 The detection performance of small objects in remote sensing images is not satisfactory compared to large objects, especially in low-resolution and noisy images.
Chao, Dennis +4 more
core +1 more source
Small Object Detection Based on Stereo Vision
International Journal of Automotive Engineering, 2016 Small size objects which dimensions are around 0.15m are one of the major security risks to driving vehicles in the highway. Lidar and radar are hard to detect this kind of objects due to the sparsity of their detecting signal.
Long Qian +4 more
doaj +1 more source
Detecting Small Signs from Large Images
, 2017 In the past decade, Convolutional Neural Networks (CNNs) have been demonstrated successful for object detections. However, the size of network input is limited by the amount of memory available on GPUs. Moreover, performance degrades when detecting small
Chen, Min +4 more
core +1 more source
Skip DETR: end-to-end Skip connection model for small object detection in forestry pest dataset
Frontiers in Plant Science, 2023 Object detection has a wide range of applications in forestry pest control. However, forest pest detection faces the challenges of a lack of datasets and low accuracy of small target detection.
Bing Liu +5 more
doaj +1 more source