Results 101 to 110 of about 54,995 (246)

Dynamic Adaptive Label Assignment for Tiny Object Detection in Remote Sensing Images

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT With the development of unmanned aerial vehicle and satellite technology, the application of tiny object detection in remote sensing images is becoming increasingly widespread. Although significant progress has been made in the accuracy and speed of object detection in recent years, performance declines sharply when general object detectors ...
Shuohao Shi, Qiang Fang, Xin Xu
wiley   +1 more source

A Pine Wilt Disease Detection Model Integrated with Mamba Model and Attention Mechanisms Using UAV Imagery

open access: yesRemote Sensing
Pine wilt disease (PWD) is a highly destructive worldwide forest quarantine disease that has the potential to destroy entire pine forests in a relatively brief period, resulting in significant economic losses and environmental damage.
Minhui Bai   +4 more
doaj   +1 more source

AVCLNet: Multimodal Multispeaker Tracking Network Using Audio‐Visual Contrastive Learning

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Audio‐visual speaker tracking aims to determine the locations of multiple speakers in the scene by leveraging signals captured from multisensor platforms. Multimodal fusion methods can improve both the accuracy and robustness of speaker tracking.
Yihan Li   +5 more
wiley   +1 more source

GY-YOLO: ghost separable YOLO for pedestrian detection

open access: yesNeural Computing and Applications
Abstract In recent years, there has been impressive development in human detection. The main challenge in pedestrian detection is the training data. To assess detectors in crowd scenarios more effectively, a novel dataset in this study called the HEP dataset (Hybrid Egyptian Pedestrian dataset) is introduced. The HEP dataset is extensive, has
Ali M. Elhenidy   +3 more
openaire   +1 more source

FD-YOLO: A YOLO Network Optimized for Fall Detection

open access: yesApplied Sciences
Falls are defined by the World Health Organization (WHO) as incidents in which an individual unintentionally falls to the ground or a lower level. Falls represent a serious public health issue, ranking as the second leading cause of death from unintentional injuries, following traffic accidents.
Hoseong Hwang, Donghyun Kim, Hochul Kim
openaire   +2 more sources

MSFFNet: Multiscale Feature Fusion Network for Small Target Detection in Remote Sensing Images

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT With the advancement of satellite remote sensing technology, object detection based on high‐resolution remote sensing imagery has emerged as a prominent research focus in the field of computer vision. Although numerous algorithms have been developed for remote sensing image object detection, they still suffer from challenges such as low ...
Hui Zong   +5 more
wiley   +1 more source

DWYL? YOLO... [PDF]

open access: yesAnnals of Leisure Research, 2014
openaire   +1 more source

YOLO-HF: Early Detection of Home Fires Using YOLO

open access: yesIEEE Access
Domestic fires (residential and indoor) result in substantially higher deaths compared to other types of conflagrations, making early detection crucial to minimizing the loss of life and property. Existing studies and datasets predominantly focus on wildfire detection, with few datasets that capture the complexity of indoor environments and the subtle ...
Bo Peng, Tae-Kook Kim
openaire   +2 more sources

RAGLRO: Retrieval‐Augmented Generation With Large Language Models for Robotic Operations

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT To enable autonomous operations in complex industrial environments, this paper proposes retrieval‐augmented generation with large language models for robotic operations (RAGLRO), a robotic framework specifically designed for power switchgear operation tasks.
Wenrui Wang   +6 more
wiley   +1 more source

YOLO‐GDCNN: Real‐Time Operating Point Detection for Live Working Robots in the Power Industry

open access: yesHigh Voltage, EarlyView.
ABSTRACT In the power industry maintenance, the capability of live working robots to detect and operate with power components in real time is paramount. This paper proposes a cascaded detection framework for real‐time detection of live working operation points, named YOLO‐GDCNN. The framework consists of two parts.
Haoning Zhao   +7 more
wiley   +1 more source

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