Results 241 to 250 of about 113,519 (298)

A UAV‐based deep learning pipeline for intertidal macrobenthos monitoring: Behavioral and age classification in Tachypleus tridentatus

Remote Sensing in Ecology and Conservation, EarlyView.
The endangered tri‐spine horseshoe crab (Tachypleus tridentatus), a “living fossil” crucial to coastal ecology and biomedical research, is experiencing severe population declines. Effective conservation requires efficient monitoring, which traditional methods cannot deliver at scale. We develop an integrated UAV deep learning framework tailored to this
Xiaohai Chen, Yuyuan Bao, Ziwei Ying, Mujiao Xie, Ting Li, Jixing Zou, Jun Shi, Xiaoyong Xie   +7 more
wiley   +1 more source

Customs fraud detection using a gradient boosting approach for joint classification and risk estimation. [PDF]

Sci Rep
Alwanin R, Ismail MMB, Bchir O.
europepmc   +1 more source

How to grow new applications out of old research? Evidence from firm cumulative investments in deep learning

Strategic Management Journal, EarlyView.
Abstract Research Summary Firm technological research has the potential to spawn multiple applications. Despite recognizing such potential, past literature disagrees on the process through which firms discover and grow new applications out of their past technological research.
Xirong (Subrina) Shen
wiley   +1 more source

Leveraging productivity indicators for anomaly detection in swine breeding herds with unsupervised learning. [PDF]

Front Vet Sci
Pedro Mil-Homens M, Wang C, Trevisan G, Dórea F, Linhares DCL, Holtkamp D, Silva GS.   +6 more
europepmc   +1 more source

Fail‐Controlled Classifiers: A Swiss‐Army Knife Toward Trustworthy Systems

Software: Practice and Experience, EarlyView.
ABSTRACT Background Modern critical systems often require to take decisions and classify data and scenarios autonomously without having detrimental effects on people, infrastructures or the environment, ensuring desired dependability attributes. Researchers typically strive to craft classifiers with perfect accuracy, which should be always correct and ...
Fahad Ahmed Khokhar, Tommaso Zoppi, Andrea Ceccarelli, Leonardo Montecchi, Andrea Bondavalli   +4 more
wiley   +1 more source

Research on the automation of intelligent accounting information processing process driven by neural networks. [PDF]

Sci Rep
Cai M.
europepmc   +1 more source

Autoencoder-Driven State-of-Health Estimation for Lithium-Ion Batteries via Dynamic Relaxation Time Distribution Features from Electrochemical Impedance Spectroscopy

Qian Xu, Mingyao Ma, Jiang Tingzhi, Wu Jiacheng   +3 more
openalex   +1 more source

Distributed AutoML framework for multi‐objective optimization of concrete crack segmentation models

Structural Concrete, EarlyView.
Abstract Monitoring cracks in concrete surfaces is essential for structural safety. While machine vision techniques have received significant interest in this domain, selecting optimal models and tuning hyperparameters remain challenging. This paper proposes a Distributed Automated Machine Learning (AutoML) framework for efficiently designing and ...
Armin Dadras Eslamlou, Shiping Huang, Belén Riveiro, M. Z. Naser   +3 more
wiley   +1 more source

Masked autoencoder-based self-supervised learning for forest plant classification

Luu Van Huy, Nguyen Huy Tuong, Le Hoang Ngoc Han, Nguyễn Văn Hiệu   +3 more
openalex   +2 more sources

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source