Results 61 to 70 of about 14,783 (197)

Artificial Intelligence in Periodontology: A Systematic Review

Journal of Periodontal Research, EarlyView.
AI shows promise across periodontology, with deep learning achieving strong performance for image‐based diagnosis of periodontitis. However, limited data diversity, inconsistent metrics, and scarce external validation raise concerns about generalizability and clinical applicability.
Antonin Tichy, Nils Werner, Helena Dujic, Charlotte Wetzel, Vinay Pitchika, Caspar Victor Bumm, Matthias Folwaczny, Falk Schwendicke   +7 more
wiley   +1 more source

JALAD: Joint Accuracy- and Latency-Aware Deep Structure Decoupling for Edge-Cloud Execution

, 2018
Recent years have witnessed a rapid growth of deep-network based services and applications. A practical and critical problem thus has emerged: how to effectively deploy the deep neural network models such that they can be executed efficiently ...
Hu, Chenghao, Jiang, Jingyan, Li, Hongshan, Wang, Zhi, Wen, Yonggang, Zhu, Wenwu   +5 more
core   +1 more source

Automated Tuberculosis Detection in Chest Radiographs: A Hybrid Deep Learning Framework for Clinical Decision Support

Applied AI Letters, Volume 7, Issue 2, June 2026.
A hybrid deep learning framework integrating VGG16, ResNet50, and DenseNet121 is proposed for automated tuberculosis detection from chest X‐ray images. Feature‐level fusion enhances robustness and generalization, achieving 97.4% accuracy across multiple public datasets, supporting reliable clinical decision‐making in resource‐limited healthcare ...
Md. Tahmid Hossain, Hrittik Mural, Monowar Wadud Hridoy   +2 more
wiley   +1 more source

U-Net-based VGG19 model for improved facial expression recognition

工程科学学报
In response to the challenges faced by traditional facial recognition techniques, such as insufficient focus on key channel features, large number of parameters, and low recognition accuracy, this study proposes an improved VGG19 model that incorporates ...
Xiaohu ZHAO, Jingyi ZHANG, Mingzhi JIAO, Lixun XIE, Lanfei WANG, Weiqing SUN, Di ZHANG   +6 more
doaj   +1 more source

An Effective Ensemble Convolutional Learning Model with Fine-Tuning for Medicinal Plant Leaf Identification

Information, 2023
Accurate and efficient medicinal plant image classification is of utmost importance as these plants produce a wide variety of bioactive compounds that offer therapeutic benefits.
Mohd Asif Hajam, Tasleem Arif, Akib Mohi Ud Din Khanday, Mehdi Neshat   +3 more
doaj   +1 more source

Loom: Exploiting Weight and Activation Precisions to Accelerate Convolutional Neural Networks

, 2018
Loom (LM), a hardware inference accelerator for Convolutional Neural Networks (CNNs) is presented. In LM every bit of data precision that can be saved translates to proportional performance gains.
Judd, Patrick, Lascorz, Alberto Delmas, Moshovos, Andreas, Sharify, Sayeh, Siu, Kevin   +4 more
core   +1 more source

The Rise of Human–Computer Integration in Marketing: A Theory Synthesis

Psychology &Marketing, Volume 43, Issue 6, Page 1343-1380, June 2026.
ABSTRACT Human–computer integration (HCInt) technologies, which merge human bodily, cognitive, and sensory functions with computational processes, are reshaping the foundations of consumer experience. Unlike traditional human–computer interaction, HCInt entails adaptive and reciprocal coupling through AI‐driven augmentation, wearables, muscle–computer ...
Carlos Velasco, Kosuke Motoki, Olivia Petit, Aram Nikolai Andersen, Marzieh Alaei, Anders Gustafsson   +5 more
wiley   +1 more source

Single-modality and joint fusion deep learning for diabetic retinopathy diagnosis

Scientific African, 2022
The current study evaluated and compared single-modality and joint fusion deep learning approaches for automatic binary classification of diabetic retinopathy (DR) using seven convolutional neural network models (VGG19, ResNet50V2, DenseNet121 ...
Sara El-Ateif, Ali Idri
doaj   +1 more source

Comparison Efficacy of VGG16 and VGG19 Insect Classification Models

JIKO (Jurnal Informatika dan Komputer), 2023
This study compares two popular deep-learning models, VGG16 and VGG19, for insect classification. This study aims to evaluate insect detection architectures to automate insect identification. We use a large, heterogeneous dataset of insect species, including common pests and beneficial insects, and their images to achieve this goal.
Djarot Hindarto, Nihayah Afarini, Endah T Esthi H   +2 more
openaire   +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