Results 101 to 110 of about 9,112 (254)

Vision language models for bridge inspections: A review of applications in image‐based damage documentation

Structural Concrete, EarlyView.
Abstract Automating bridge inspections requires more than detecting individual damage instances. It demands systems capable of describing, contextualizing, and interpreting damage in an inspection‐relevant manner. Conventional computer vision approaches, such as object detection and segmentation, primarily address visual recognition tasks and are ...
Rona Firdes Çelik, Ulas Bagci, Sylvia Kessler   +2 more
wiley   +1 more source

Efficient method for DCT-domain image arbitrary downsampling

Tongxin xuebao, 2007
A novel approach to resize Images with m/n resizing ratio in the DCT domain,was proposed which expoits the relationship of DCT coefficients between m 2input blocks and n 2output blocks.Experimental results confirm that the scheme performs about 0.5dB ...
DU Yao-gang1, CAI An-ni2
doaj   +2 more sources

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

AML‐Net: Attention‐based multi‐scale lightweight model for brain tumour segmentation in internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam, Basit Raza, Muhammad Faheem, Aadil Raza   +3 more
wiley   +1 more source

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang, Jian Yang, Bob Zhang, Yang Tang, Wenli Du, Bihan Wen   +5 more
wiley   +1 more source

Edge‐Channel Aggregation Network and Two‐Stage Fine Tuning Scheme for Handwritten Dongba Character Recognition

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Handwritten Dongba Character Recognition (HDCR) contains a large number of visually similar characters with subtle and fragile edge cues, posing severe challenges to feature learning. To address this issue, an Edge Channel Aggregation Network (EdgeCANet) model is proposed.
Xiali Li, Yang Xiao, Xiaojun Bi, Yanlong Luo   +3 more
wiley   +1 more source

Align What Truly Matters: Pedestrian‐Relevant Hierarchical Parsing Network for Text‐Based Person Retrieval

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Fine‐grained alignment is crucial for text‐based person retrieval, which searches for relevant pedestrian images using a text query. However, background clutter and semantically vacuous words can cause interference and misalignment, hindering retrieval performance.
Jiajun Su, Yifan Shi, Pudu Liu, Jianqing Zhu, Huanqiang Zeng, Liu Liu, Zhen Lei   +6 more
wiley   +1 more source

Deep blueprint: A literature review and guide to automated image classification for ecologists

Journal of Animal Ecology, EarlyView.
A practical, literature‐grounded review that gives ecologists a clear, modular workflow for deep learning image classification. With code, GUIs and a novel deep sea case study (automated deep sea biotope classification) it lowers technical barriers and provides a usable blueprint for accelerating, standardising, and scaling ecological image analysis ...
Chloe A. Game, Nils Piechaud, Kerry L. Howell   +2 more
wiley   +1 more source

Small Object Detection Method for Bioimages Based on Improved YOLOv8n Model

Integrative Zoology, EarlyView.
This study proposes a small object detection method for bioimages based on an improved YOLOv8n model. Experimental results demonstrate that the proposed approach effectively enhances detection precision, recall, and mAP50, offering a novel solution for the technical challenges in biological microscopy research.
Xiaoyu Li, Chengrui Shang, Xian Hou, Qi Wang, Jiao Wang, Taxing Zhang, Xiangjiang Zhan, Shengkai Pan   +7 more
wiley   +1 more source

Efficient Masked Autoencoder for Birdsong Representation with Applications on Wild Bird Species Classification

Integrative Zoology, EarlyView.
Research on mosquito feeding preferences and the malaria parasites they transmit is essential for understanding the interactions between hosts, vectors, and parasites. In this study, vertebrate hosts were identified in 72 mosquitoes. Most blood meals (58.7%) came from birds, representing 25 species, while 40.0% came from mammals (13 species), and 1.3 ...
Qin Zhang, Shipeng Hu, Hengrui Wang, Jizheng Yi, Guoxiong Zhou, Xiangyu Shen, Weixiong Peng, Zhishu Xiao, Aibin Chen   +8 more
wiley   +1 more source