Results 51 to 60 of about 17,494 (194)

Sustainable Live Sound Monitoring and Classification System Enabled by a Triboelectric Nanogenerator and Machine Learning Techniques

ENERGY &ENVIRONMENTAL MATERIALS, Volume 9, Issue 3, May 2026.
A high‐performance Triboelectric Nanogenerator (TENG) acoustic sensor using polyimine/graphite polypropylene (PI/GP) was developed for real‐time, sustainable sound monitoring and classification. The self‐powered device delivers 25.67 μW output power, 92.7% accuracy with MobileNet V1, and powers a wireless transmission circuit, demonstrating dual ...
Majid Haji Bagheri, Araz Rajabi‐Abhari, Owen Gibbs, Pengcheng Xi, Asif Abdullah Khan, Fangzheng Huang, Md Soyaeb Hassan, Ning Yan, Dayan Ban   +8 more
wiley   +1 more source

Research on Power Quality Prediction in Low-Voltage Distribution Areas for Photovoltaic Grid-Connection Based on XTimesNet

Journal of Harbin University of Science and Technology
Aiming at the problem of low power quality prediction accuracy in PV grid-connected low-voltage stations, this paper proposes an XTimesNet prediction model for power quality steady-state index.
LIU Xiaokang, WANG Jianhua, LI Pengfei, CUI Qi   +3 more
doaj   +1 more source

Deep Learning Integration in Optical Microscopy: Advancements and Applications

Microscopy Research and Technique, Volume 89, Issue 5, Page 791-814, May 2026.
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari, Sagnika Dutta, H. Deeksha, Samreen A. Patel, Budheswar Dehury, Nirmal Mazumder   +5 more
wiley   +1 more source

Recognition of Sugarcane Leaf Diseases in Complex Backgrounds Based on Deep Network Ensembles

智慧农业
[Objective]Sugarcane is an important cash crop, and its health status affects crop yields. However, under natural environmental conditions, the identification of sugarcane leaf diseases is a challenging problem.
MA Weiwei, CHEN Yue, WANG Yongmei
doaj   +1 more source

AI‐Enabled Imaging for Pathogen Detection Under Stress Conditions: A Systematic Review

Comprehensive Reviews in Food Science and Food Safety, Volume 25, Issue 3, May 2026.
ABSTRACT Advances in pathogen detection that incorporate artificial intelligence (AI) may capture microbial signals under challenging environmental conditions that traditional methods miss. This systematic review evaluates the application, performance, and methodological characteristics of AI‐enabled imaging for pathogen detection, including its impact
MeiLi Papa, Gillian Kuehnle, Yoo Jung (Erika) Oh, Jiyoon Yi   +3 more
wiley   +1 more source

Deep Learning-Based Soybean Leaf Disease Classification Using DenseNet121, Xception, and MobileNetV2

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
This study is driven by the challenge of soybean leaf diseases, which significantly reduce agricultural productivity and pose a threat to food security.
Nita Helmawati, Yopy Tri Buana, Eko Rahmad Darmawan, Kusrini Kusrini   +3 more
doaj   +1 more source

On the Optimal Selection of Mel‐Frequency Cepstral Coefficients for Voice Deepfake Detection

Expert Systems, Volume 43, Issue 5, May 2026.
ABSTRACT The continuous evolution of techniques for generating manipulated audio, known as voice deepfakes, and the widespread availability of tools that produce convincing forgeries have created an urgent need for reliable detection methods. This work considers the dimensionality of Mel‐Frequency Cepstral Coefficients (MFCCs) as a core design variable
Sergio A. Falcón‐López, Llanos Tobarra, Antonio Robles‐Gómez, Rafael Pastor‐Vargas   +3 more
wiley   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, Volume 13, Issue 4, Page 747-754, April 2026.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Fully automated determination of the cervical vertebrae maturation stages using deep learning with directional filters.

PLoS ONE, 2022
IntroductionWe aim to apply deep learning to achieve fully automated detection and classification of the Cervical Vertebrae Maturation (CVM) stages. We propose an innovative custom-designed deep Convolutional Neural Network (CNN) with a built-in set of ...
Salih Furkan Atici, Rashid Ansari, Veerasathpurush Allareddy, Omar Suhaym, Ahmet Enis Cetin, Mohammed H Elnagar   +5 more
doaj   +1 more source

From channel‐spatial attention to state space models: A review of evolving mechanisms in tumour segmentation

Clinical and Translational Discovery, Volume 6, Issue 2, April 2026.
This review summarises the evolution of attention mechanisms for tumour segmentation—from pre‐Transformer modules to Transformer self‐attention and emerging Mamba‐based state space models—highlighting their roles in feature enhancement, long‐range dependency modelling, and their potential to advance next‐generation intelligent segmentation in clinical ...
Yanfei Sun, Junyu Wang, Rui Yin
wiley   +1 more source