Results 41 to 50 of about 458,168 (313)
Drones, 2022 To solve the problem of low detection accuracy of small objects in UAV optical remote sensing images due to low contrast, dense distribution, and weak features, this paper proposes a small object detection method based on feature alignment of candidate ...
Jinkang Wang +3 more
doaj +1 more source
Visual SLAM and Moving-object Detection for a Small-size Humanoid Robot [PDF]
, 2010 In the paper, a novel moving object detection (MOD) algorithm is developed and integrated with robot visual Simultaneous Localization and Mapping (vSLAM).
Rung-Chi Ju +2 more
core +1 more source
Fire-RPG: An Urban Fire Detection Network Providing Warnings in Advance
FireUrban fires are characterized by concealed ignition points and rapid escalation, making the traditional methods of detecting early stage fire accidents inefficient.
Xiangsheng Li, Yongquan Liang
doaj +1 more source
Remote Sensing, 2023 Vehicle detection based on unmanned aerial vehicle (UAV) aerial images plays a significant role in areas such as traffic monitoring and management, disaster relief, and more, garnering extensive attention from researchers in recent years.
Mian Pan +5 more
doaj +1 more source
Multi-View Object Detection Based on Deep Learning
Applied Sciences, 2018 A multi-view object detection approach based on deep learning is proposed in this paper. Classical object detection methods based on regression models are introduced, and the reasons for their weak ability to detect small objects are analyzed. To improve
Cong Tang +4 more
doaj +1 more source
SF-YOLOv5: A Lightweight Small Object Detection Algorithm Based on Improved Feature Fusion Mode
Sensors, 2022 In the research of computer vision, a very challenging problem is the detection of small objects. The existing detection algorithms often focus on detecting full-scale objects, without making proprietary optimization for detecting small-size objects. For
Haiying Liu +3 more
doaj +1 more source
Small Object Detection with Multiscale Features [PDF]
International Journal of Digital Multimedia Broadcasting, 2018 The existing object detection algorithm based on the deep convolution neural network needs to carry out multilevel convolution and pooling operations to the entire image in order to extract a deep semantic features of the image. The detection models can get better results for big object.
Guo X. Hu +4 more
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen +23 more
wiley +1 more source
Why does brain damage impair memory? A connectionist model of object recognition memory in perirhinal cortex [PDF]
, 2006 Object recognition is the canonical test of declarative memory, the type of memory putatively impaired after damage to the temporal lobes. Studies of object recognition memory have helped elucidate the anatomical structures involved in declarative memory,
Bussey, Timothy J. +2 more
core +1 more source
Adaptive Feature Fusion for Small Object Detection [PDF]
, 2022 In order to alleviate the situation that small objects are prone to missed detection and false detection in natural scenes, this paper proposed a small object detection algorithm for adaptive feature fusion, referred to as MMF-YOLO.
Xiuwen Lu, Hongying Zhang, Qi Zhang
core +1 more source