Results 181 to 190 of about 24,057 (250)

Seasonal variations and challenges in estimating populations and identifying species of Korean ungulates using drone‐derived thermal orthomosaic maps

Wildlife Biology, EarlyView.
Drones equipped with thermal infrared (TIR) cameras offer significant time and labor savings in estimating wild ungulate populations. However, accurately monitoring forest‐dwelling ungulates remains challenging due to their elusive behavior and complex habitat.
Jinhwi Kim, Donggul Woo
wiley   +1 more source

Monitoring wildlife using long‐endurance solar‐electric UAVs

Wildlife Biology, EarlyView.
This report discusses the effectiveness of using small solar‐electric UAV (uncrewed aerial vehicles) for aerial wildlife monitoring. We review four years of aerial wildlife monitoring missions using a 5.5‐m wingspan, solar‐electric UAV that was equipped with a gimballed IR/RGB camera.
Götz Bramesfeld, William Bissonnette, Maya Rahaman‐Noronha, Kanwar Johal   +3 more
wiley   +1 more source

Evaluating machine learning models for multi‐species wildlife detection and identification on remote sensed nadir imagery in South African savanna

Wildlife Biology, EarlyView.
This research paper investigates the efficacy of leading machine learning (ML) models for detecting and identifying ungulate species in African savanna using nadir imagery from unmanned aerial vehicles (UAVs). Traditional aerial counting methods, while widely used, suffer from significant limitations in accuracy and precision, in part due to human ...
Paul Allin, Fadel Seydou, Radloff Frans, Andrew Davies, Alison Leslie   +4 more
wiley   +1 more source

Estimating red deer Cervus elaphus population density using drones in a steep and rugged terrain

Wildlife Biology, EarlyView.
Precise and accurate information about population density, crucial for wildlife management, is difficult to obtain for elusive species living in dense forests or steep and inaccessible terrain. Using unmanned aerial vehicles (UAVs), we developed a method for obtaining absolute population estimates of ungulates living in steep, rugged, and partly ...
Julie Bommerlund, Torbjørn Ergon, Simon Filhol, Atle Mysterud   +3 more
wiley   +1 more source

Multi‐Vine Disease Prediction in a Field Test Spanning Whole Growth Season at Wine‐Industrial Site (McLaren Vale)

Artificial Intelligence for Engineering, EarlyView.
Overall, the findings provide reliable evidence for block‐level disease early warning, inspection prioritisation, and spray decision‐making, helping to reduce unnecessary inputs, lower environmental burdens, and improve the resilience and sustainability of vineyard production systems.
Shu Liang, Nguyen Van Duc Long, Mst Irin Parvin, Philip Kwong, Vinay Pagay, Maria Maglieri, Steve Maglieri, Andrew Godfrey, Harpinder Sandhu, Kartheek Munigoti, Nicola Sasanelli, Pieter van Schalkwyk, Freya Richardson, Bhola Paudel, Pramod Gautam, Kashif Khaqan, Volker Hessel   +16 more
wiley   +1 more source

VDNeRF: Vision‐Only Dynamic Neural Radiance Field for Urban Scenes

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Neural radiance fields (NeRFs) implicitly model continuous three‐dimensional scenes using a set of images with known camera poses, enabling the rendering of photorealistic novel views. However, existing NeRF‐based methods encounter challenges in applications such as autonomous driving and robotic perception, primarily due to the difficulty of ...
Zhengyu Zou, Jingfeng Li, Hao Li, Xiaolei Hou, Jinwen Hu, Jingkun Chen, Lechao Cheng, Dingwen Zhang   +7 more
wiley   +1 more source

CDFNet: Cross‐Modal Deep Fusion for Monocular 3D Semantic Scene Completion

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Semantic scene completion (SSC) aims to predict the semantic occupancy and geometry of 3D scenes. Recently, most studies focus on camera‐based approaches due to the rich visual cues of images and the cost‐effectiveness of cameras. However, these methods usually lack efficient fusion and fine‐grained processing of cross‐modal semantic ...
Xianjing Cheng, Lintai Wu, Jie Wen, Tianhao Peng, Yong Xu, Zairong Wei   +5 more
wiley   +1 more source

SFK: Shape‐ and Function‐Grounded Keypoint Representation for Sequential Manipulation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Sequential manipulation is the process by which robots perform multiple interdependent steps to accomplish composite tasks, demanding tight integration of perception, planning and execution. Existing methods incorporate explicit features such as category, semantics, 6D pose or affordance to enhance consistency, yet single‐feature ...
Yaxin Liu, Yan Liu, Xinyu Song, Ruiqing Han, Haiyong Liu, Bo Huang, Yufeng Yao, Ming Zhong   +7 more
wiley   +1 more source

Boosting Embodied Visual Localisation Through Multi‐Granular Semantics and Multi‐Robot Consensus

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Achieving high accuracy and synergy remains extremely difficult for multi‐robot embodied visual localisation, which suffers from persistent real‐world challenges such as viewpoint ambiguity, appearance variation and dynamic occlusion. Conventional optimisation‐based methods often lead to incorrect feature matching without domain adaptation ...
Wenshuai Wang, Shiyu Liu, Peifeng Jiang, Hong Liu, Runwei Ding   +4 more
wiley   +1 more source

TMSA‐Net: Transformer‐Based Multi‐Scale Attention U‐Net for Flood Image Segmentation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Flood detection is essential for real‐time applications, including disaster management, emergency response, and alerting people in flood zones. For successful flood detection, accurate flood region segmentation is essential. However, the flood region segmentation is challenging due to the complex background and occlusions with debris and the ...
Parham Imanzadeh Charandabi, Shivakumara Palaiahnakote, Apostolos Antonacopoulos, Christian Clausner   +3 more
wiley   +1 more source