Results 121 to 130 of about 7,363,707 (395)

Skip DETR: end-to-end Skip connection model for small object detection in forestry pest dataset

open access: yesFrontiers 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

Plug & Play Convolutional Regression Tracker for Video Object Detection [PDF]

open access: yesarXiv, 2020
Video object detection targets to simultaneously localize the bounding boxes of the objects and identify their classes in a given video. One challenge for video object detection is to consistently detect all objects across the whole video. As the appearance of objects may deteriorate in some frames, features or detections from the other frames are ...
arxiv  

CoTDet: Affordance Knowledge Prompting for Task Driven Object Detection [PDF]

open access: yesarXiv, 2023
Task driven object detection aims to detect object instances suitable for affording a task in an image. Its challenge lies in object categories available for the task being too diverse to be limited to a closed set of object vocabulary for traditional object detection.
arxiv  

Spot‐14 and its paralog Spot‐14R regulate expression of metabolic and thermogenic pathway genes in murine brown and beige adipocytes

open access: yesFEBS Letters, EarlyView.
Spot‐14 and Spot‐14R play distinct roles in regulating metabolism in brown and beige adipocytes. While both influence lipid and glucose pathways, Spot‐14 uniquely controls thermogenic gene expression. This dual regulation balances energy storage and heat production, highlighting potential therapeutic targets for obesity and metabolic disorders. Spot 14
Lidia Itzel Castro‐Rodríguez   +3 more
wiley   +1 more source

Object detection model of coal mine rescue robot based on multi -scale feature fusio

open access: yesGong-kuang zidonghua, 2020
Traditional object detection model uses artificial object features, resulting in poor detection accuracy. Object detection model based on deep learning has high detection accuracy.
ZHAI Guodong   +5 more
doaj   +1 more source

Interaction vesicles as emerging mediators of host‐pathogen molecular crosstalk and their implications for infection dynamics

open access: yesFEBS Letters, EarlyView.
Interaction extracellular vesicles (iEVs) are hybrid vesicles formed through host‐pathogen communication. They facilitate immune evasion, transfer pathogens' molecules, increase host cell uptake, and enhance virulence. This Perspective article illustrates the multifunctional roles of iEVs and highlights their emerging relevance in infection dynamics ...
Bruna Sabatke   +2 more
wiley   +1 more source

Improving object detection by enhancing the effect of localisation quality evaluation on detection confidence

open access: yesIET Computer Vision
The one‐stage object detector has been widely applied in many computer vision applications due to its high detection efficiency and simple framework.
Zuyi Wang, Wei Zhao, Li Xu
doaj   +1 more source

Review of One-Stage Universal Object Detection Algorithms in Deep Learning [PDF]

open access: yesJisuanji kexue yu tansuo
In recent years, object detection algorithms have gradually become a hot research direction as a core task in the field of computer vision. They enable computers to recognize and locate target objects in images or video frames, and are widely used in ...
WANG Ning, ZHI Min
doaj   +1 more source

Review of IoT Sensor Systems Used for Monitoring the Road Infrastructure

open access: yesSensors, 2023
An intelligent transportation system is one of the fundamental goals of the smart city concept. The Internet of Things (IoT) concept is a basic instrument to digitalize and automatize the process in the intelligent transportation system.
Kristian Micko   +2 more
doaj   +1 more source

RRPN: Radar Region Proposal Network for Object Detection in Autonomous Vehicles [PDF]

open access: yes, 2019
Region proposal algorithms play an important role in most state-of-the-art two-stage object detection networks by hypothesizing object locations in the image. Nonetheless, region proposal algorithms are known to be the bottleneck in most two-stage object detection networks, increasing the processing time for each image and resulting in slow networks ...
arxiv   +1 more source

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