Results 161 to 170 of about 16,046 (295)

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao   +10 more
wiley   +1 more source

Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models

open access: yesInternational Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel   +2 more
wiley   +1 more source

Integrating multimodal data and machine learning for entrepreneurship research

open access: yesStrategic Entrepreneurship Journal, EarlyView.
Abstract Research Summary Extant research in neuroscience suggests that human perception is multimodal in nature—we model the world integrating diverse data sources such as sound, images, taste, and smell. Working in a dynamic environment, entrepreneurs are expected to draw on multimodal inputs in their decision making.
Yash Raj Shrestha, Vivianna Fang He
wiley   +1 more source

Organizing across cognitive asymmetry in human–AI collaboration: A study of perfume creation

open access: yesStrategic Management Journal, EarlyView.
Abstract Research Summary As organizations increasingly adopt generative AI (GenAI), they face a strategic challenge: not only deciding which tasks AI should perform, but also how to organize the integration of human and AI efforts to produce viable solutions.
Tomoko Yokoi   +3 more
wiley   +1 more source

A Novel Federated Learning Scheme for Generative Adversarial Networks

open access: yes
Generative adversarial networks (GANs) have been advancing and gaining tremendous interests from both academia and industry. With the development of wireless technologies, a huge amount of data generated at the network edge provides an unprecedented ...
Yu, Keping   +5 more
core   +1 more source

A Systems‐Level Approach to Address Risks and Ethics in Artificial Intelligence Systems

open access: yesSystems Engineering, EarlyView.
ABSTRACT Artificial intelligence (AI) is rapidly changing the world, from completely controlling routine or mundane tasks like text and image generation, to powering advanced algorithms that control critical systems. The recent advances in generative AI quickly overwhelmed multiple industries from education to finance as first adopters rushed (and ...
Vincent P. Paglioni, Torrey Mortenson
wiley   +1 more source

Artificial Intelligence in Voice Disorders: Current Landscape, Emerging Applications and Future Directions

open access: yesWorld Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
ABSTRACT Objective To provide a comprehensive review of the current landscape of artificial intelligence (AI) applications in voice disorder, with emphasis on emerging applications, limitations, and future directions for clinical integration. Methods Literature review.
Rachel B. Kutler, Anaïs Rameau
wiley   +1 more source

Pickin' up good vibrations: a systematic review of footfall detection and analysis in the realm of wildlife surveying

open access: yesWildlife Biology, EarlyView.
Exploration of new wildlife surveying methodologies that leverage advances in sensor technology and machine learning has led to tentative research into the application of seismology techniques. This, most commonly, involves the deployment of a footfall trap – a seismic sensor and data logger customised for wildlife footfall.
Benjamin J. Blackledge   +4 more
wiley   +1 more source

Lightweight Convolutional Neural Networks Model and Data Augmentation‐Based Background Regression for Rail Surface Defect Detection

open access: yesArtificial Intelligence for Engineering, EarlyView.
An ultra‐lightweight semantic segmentation network RailNet with only 0.905 M parameters is proposed for rail surface defect detection. Combined with a CDBM image enhancement and GAN‐based data augmentation, RailNet achieves superior segmentation accuracy and real‐time speed on edge devices.
Ziqing Wu   +4 more
wiley   +1 more source

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