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Rethinking the Inception Architecture for Computer Vision

Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens et al. • arXiv (Cornell University) (2015)

Convolutional networks are at the core of most state-of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains in various benchmark...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1512.00567

Vision-Based Trajectory Generation and Kinematic Modeling for Human-like Grasp Reproduction in a Robotic Prosthetic Hand

Renzo Fernández, Néstor Zamora, Victor Coloma, Nino Vega et al. • Technologies (2026)

The use of prosthetic devices can significantly improve the quality of life of individuals with limb amputations. However, existing prosthetic hands face multiple engineering and manufacturing challenges, making them economically inaccessib...

DOAJ Open Access (DOAJ) DOI: 10.3390/technologies14060334

Rethinking the Inception Architecture for Computer Vision

Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens et al. • IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (2016)

Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains in various benchmark...

OPENALEX DOI: https://doi.org/10.1109/cvpr.2016.308

Multimodal Phase-Space Dynamics Fusion for Robust Ischemia Screening: An Edge-AI Paradigm with SERF Magnetocardiography

Keyi Li, Xiangyang Zhou, Yifan Jia, Ruizhe Wang et al. • Biosensors (2026)

Background: Myocardial ischemia (MI) is a major cause of morbidity and mortality worldwide and requires timely and reliable detection. Although Spin-Exchange Relaxation-Free (SERF) magnetocardiography (MCG) provides femtotesla-level sensiti...

DOAJ Open Access (DOAJ) DOI: 10.3390/bios16040228

From Data to Decisions: AI in Varicose Veins—Predicting, Diagnosing, and Guiding Effective Management

Lakshmi Sree Pugalenthi, Chris Garapati, Srivarshini Maddukuri, Fnu Kanwal et al. • Journal of Vascular Diseases (2025)

Background: Varicose veins (VVs) of the lower limbs, characterized by palpable, dilated, and tortuous veins, affect 2–73% of the global population. Artificial intelligence (AI) offers significant potential to enhance healthcare efficiency a...

DOAJ Open Access (DOAJ) DOI: 10.3390/jvd4020019

Hybrid Deep Learning Algorithms for Dog Breed Identification—A Comparative Analysis

B. Valarmathi, N. Srinivasa Gupta, G. Prakash, R. Hemadri Reddy et al. • IEEE Access (2023)

Deep learning and computer vision algorithms will be applied to find the breed of the dog from an image. The goal is to have the user submit an image of a dog, and the model will choose one of the 120 breeds stated in the dataset to determi...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3297440

Crowd Analysis Using Computer Vision Techniques

Julio C. S. Jacques, Soraia Raupp Musse, Cláudio R. Jung • IEEE Signal Processing Magazine (2010)

This article presents a survey on crowd analysis using computer vision techniques, covering different aspects such as people tracking, crowd density estimation, event detection, validation, and simulation. It also reports how related the ar...

OPENALEX Open Access DOI: https://doi.org/10.1109/msp.2010.937394

New topic horizons for drone systems and applications

Karen Anderson, Brandi M. Shabaga, Serge Wich, Geoff Fink et al. • Drone Systems and Applications (2023)

Summary This journal (Drone Systems and Applications; DSA) conducted a targeted “horizon scan” during 2022 within our team of editors and associate editors. We asked—Which research areas currently under-represented in Drone Systems and Appl...

DOAJ Open Access (DOAJ) DOI: 10.1139/dsa-2023-0019

Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics

F. Cadini, E. Zio, N. Pedroni • Science and Technology of Nuclear Installations (2008)

Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. Their use is becoming increasingly popular in the complex modeling tasks required by diagnostic, safety, and control appli...

DOAJ Open Access (DOAJ) DOI: 10.1155/2008/681890

Bayesian Regularization of Neural Networks

Frank R. Burden, David Alan Winkler • Methods in molecular biology (2008)

Bayesian regularized artificial neural networks (BRANNs) are more robust than standard back-propagation nets and can reduce or eliminate the need for lengthy cross-validation. Bayesian regularization is a mathematical process that converts ...

OPENALEX DOI: https://doi.org/10.1007/978-1-60327-101-1_3

Neural network ensembles

Lars Kai Hansen, Peter Salamon • IEEE Transactions on Pattern Analysis and Machine Intelligence (1990)

Several means for improving the performance and training of neural networks for classification are proposed. Crossvalidation is used as a tool for optimizing network parameters and architecture. It is shown that the remaining residual gener...

OPENALEX Open Access DOI: https://doi.org/10.1109/34.58871

An Improved Convolutional Neural Network (CNN) for Disease Detection and Diagnosis for Multi-crop Plants

Florence Choong Chiao Mei, Bryan Ng Jan Hong • Journal of Engineering Technology and Applied Physics (2025)

Agriculture is one of the largest sectors that contribute to the economic growth of countries, including Malaysia. However, plant diseases affect the quality of the harvest and impede farmers’ maximum yield output. Therefore, early detectio...

DOAJ Open Access (DOAJ) DOI: 10.33093/jetap.2025.7.1.2

Predicting air quality index using artificial neural network: a case study of the Coimbatore region

P. Jagadesh, J. Harshini, D. Arul, Solomon Oyebisi et al. • Discover Civil Engineering (2026)

Abstract This study predicts the Air Quality Index (AQI) in the Coimbatore region using Artificial Neural Networks (ANN) to enhance air quality management and environmental science. The researchers measured six input variables over a two-ye...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44290-026-00423-z

Predictive model for 5-year mortality after breast cancer surgery in Taiwan residents

Su-Hsin Huang, Joon-Khim Loh, Jinn-Tsong Tsai, Ming-Feng Houg et al. • Chinese Journal of Cancer (2017)

Abstract Background Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years. This study aimed to validate the use of the artificial neural network (ANN) model to predict the 5-year mortality of breast...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40880-017-0192-9

Artificial neural networks

Judith E. Dayhoff, James M. DeLeo • Cancer (2001)

Artificial neural networks now are used in many fields. They have become well established as viable, multipurpose, robust computational methodologies with solid theoretic support and with strong potential to be effective in any discipline, ...

OPENALEX Open Access DOI: https://doi.org/10.1002/1097-0142(20010415)91:8+<1615::aid-cncr1175>3.0.co;2-l

A Novel Methodology for Human Kinematics Motion Detection Based on Smartphones Sensor Data Using Artificial Intelligence

Ali Raza, Mohammad Rustom Al Nasar, Essam Said Hanandeh, Raed Abu Zitar et al. • Technologies (2023)

Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily li...

DOAJ Open Access (DOAJ) DOI: 10.3390/technologies11020055