Results 91 to 100 of about 7,363,707 (395)

A Review of Video Object Detection: Datasets, Metrics and Methods

Applied Sciences, 2020
Although there are well established object detection methods based on static images, their application to video data on a frame by frame basis faces two shortcomings: (i) lack of computational efficiency due to redundancy across image frames or by not ...
Haidi Zhu, Haoran Wei, Baoqing Li, Xiaobing Yuan, Nasser Kehtarnavaz   +4 more
doaj   +1 more source

Relation Networks for Object Detection

, 2018
Although it is well believed for years that modeling relations between objects would help object recognition, there has not been evidence that the idea is working in the deep learning era.
Dai, Jifeng, Gu, Jiayuan, Hu, Han, Wei, Yichen, Zhang, Zheng   +4 more
core   +1 more source

Described Object Detection: Liberating Object Detection with Flexible Expressions

, 2023
Detecting objects based on language information is a popular task that includes Open-Vocabulary object Detection (OVD) and Referring Expression Comprehension (REC). In this paper, we advance them to a more practical setting called Described Object Detection (DOD) by expanding category names to flexible language expressions for OVD and overcoming the ...
Xie, Chi, Zhang, Zhao, Wu, Yixuan, Zhu, Feng, Zhao, Rui, Liang, Shuang   +5 more
openaire   +2 more sources

Object-Detecting Neurons in Drosophila [PDF]

Current Biology, 2017
Many animals rely on vision to detect objects such as conspecifics, predators, and prey. Hypercomplex cells found in feline cortex and small target motion detectors found in dragonfly and hoverfly optic lobes demonstrate robust tuning for small objects, with weak or no response to larger objects or movement of the visual panorama [1-3].
Keleş, Mehmet F, Frye, Mark A
openaire   +5 more sources

Continual Detection Transformer for Incremental Object Detection

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Incremental object detection (IOD) aims to train an object detector in phases, each with annotations for new object categories. As other incremental settings, IOD is subject to catastrophic forgetting, which is often addressed by techniques such as knowledge distillation (KD) and exemplar replay (ER).
Liu, Y., Schiele, B. ; https://orcid.org/0000-0001-9683-5237, Vedaldi, A., Rupprecht, C.   +3 more
openaire   +3 more sources

UAV-YOLOv8: A Small-Object-Detection Model Based on Improved YOLOv8 for UAV Aerial Photography Scenarios

Italian National Conference on Sensors, 2023
Unmanned aerial vehicle (UAV) object detection plays a crucial role in civil, commercial, and military domains. However, the high proportion of small objects in UAV images and the limited platform resources lead to the low accuracy of most of the ...
G. Wang, Yanfei Chen, Pei An, Hanyu Hong, Jinghu Hu, Tiange Huang   +5 more
semanticscholar   +1 more source

The immunological interface: dendritic cells as key regulators in metabolic dysfunction‐associated steatotic liver disease

FEBS Letters, EarlyView.
Metabolic dysfunction‐associated steatotic liver disease (MASLD) affects nearly one‐third of the global population and poses a significant risk of progression to cirrhosis or liver cancer. Here, we discuss the roles of hepatic dendritic cell subtypes in MASLD, highlighting their distinct contributions to disease initiation and progression, and their ...
Camilla Klaimi, WanTing Kong, Camille Blériot, Joel T. Haas   +3 more
wiley   +1 more source

Aerial Data Exploration: An in-Depth Study From Horizontal to Oriented Viewpoint

IEEE Access
The development of technological devices, such as satellites and drones, has made it easier to collect images and videos from the air. From these vast data sources, the problem of detecting objects in aerial images is formed to serve situations: rescue ...
Nguyen D. Vo, Huong-Giang Ngo, Toan Le, Quang Nguyen, Danh-Du Doan, Binh Nguyen, Do Le-Huu, Nguyen Le-Duy, Huy Tran, Khanh-Duy Nguyen, Khang Nguyen   +10 more
doaj   +1 more source

Small Object Detection Based on Deep Learning for Remote Sensing: A Comprehensive Review

Remote Sensing, 2023
With the accelerated development of artificial intelligence, remote-sensing image technologies have gained widespread attention in smart cities. In recent years, remote sensing object detection research has focused on detecting and counting small dense ...
Xuan Wang, Aoran Wang, Jinglei Yi, Yongchao Song, Abdellah Chehri   +4 more
doaj   +1 more source

Regionlets for Generic Object Detection [PDF]

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013
Generic object detection is confronted by dealing with different degrees of variations, caused by viewpoints or deformations in distinct object classes, with tractable computations. This demands for descriptive and flexible object representations which can be efficiently evaluated in many locations.
Ming Yang, Xiaoyu Wang, Shenghuo Zhu, Yuanqing Lin   +3 more
openaire   +4 more sources