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Fashion Meets Computer Vision

Wen-Huang Cheng, Sijie Song, Chieh-Yun Chen, Shintami Chusnul Hidayati et al. • ACM Computing Surveys (2021)

Fashion is the way we present ourselves to the world and has become one of the world’s largest industries. Fashion, mainly conveyed by vision, has thus attracted much attention from computer vision researchers in recent years. Given the rap...

OPENALEX Open Access DOI: https://doi.org/10.1145/3447239

Low illumination image enhancement algorithm of CycleGAN coal mine based on attention mechanism and Dilated convolution

Yuanbin WANG, Yaru GUO, Jia LIU, Xu WANG et al. • Meitan kexue jishu (2024)

The complex underground environment, filled with a large amount of dust and water vapor, and uneven illumination of artificial light source, leads to problems such as low illumination and loss of detail features in images collected by under...

DOAJ Open Access (DOAJ) DOI: 10.12438/cst.2023-1597

Computer Vision

George C. Stockman, Linda G. Shapiro (2001)

From the Publisher: Computer Vision presents the necessary theory and techniques for students and practitioners who will work in fields where significant information must be extracted automatically from images. It will be a useful resource...

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Evaluating the ergonomic deficiencies in computer workstations and investigating their correlation with reported musculoskeletal disorders and visual symptoms among computer users in Bangladeshi university

Md Golam Kibria, Md Shohel Parvez, Palash Saha, Subrata Talapatra • Heliyon (2023)

Background: Nowadays, computer users are facing musculoskeletal disorders (MSDs) and visual symptoms. Prolonged sitting in inappropriate, awkward, and static postures on the computer workstation may cause musculoskeletal disorders (MSDs). S...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.heliyon.2023.e22179

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

Evaluation of Indoor Thermal Environments Using a Novel Predicted Mean Vote Model Based on Artificial Neural Networks

Xiaosai Duan, Suihuai Yu, Jianjie Chu, Dengkai Chen et al. • Buildings (2022)

The assessment of indoor thermal environments is crucial to achieving thermal comfort and energy efficiency. However, the inaccurate evaluation and strong nonlinear variations of thermal comfort parameters limit engineering designs. Therefo...

DOAJ Open Access (DOAJ) DOI: 10.3390/buildings12111880

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

Determining the Optimum Layer Combination for Cross-Laminated Timber Panels According to Timber Strength Classes Using Artificial Neural Networks

Engin Derya Gezer, Abdullah Uğur Birinci, Aydın Demir, Hasan Öztürk et al. • BioResources (2024)

The primary aim of this work was to determine the effects of production parameters, such as wood species and timber strength classes, on some mechanical properties of cross-laminated timber (CLT) panels using artificial neural network (ANN)...

DOAJ Open Access (DOAJ)

Principles of Artificial Neural Networks

Daniel Graupe • Advanced series in circuits and systems (1997)

The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and compu...

OPENALEX DOI: https://doi.org/10.1142/2982

Neural Networks for Chemists

Qingyang Xiao, Kaiyuan Liu, Yuhui Hong, Haixu Tang • ACS in focus (2024)

In recent years, breakthroughs in artificial intelligence (AI) have dramatically transformed many fields. Developments in neural networks primarily drive the advances. These powerful models have demonstrated unprecedented capabilities in le...

OPENALEX DOI: https://doi.org/10.1021/acsinfocus.7e8012

Shear banding and flow instabilities in wormlike micelles: Modelling and mechanisms – A review

Sudheesh Parathakkatt, Vaisakh Kizhuveetil, Gokul G. K., Rajashree Ajay Markandewar • eXPRESS Polymer Letters (2026)

Worm-like micelles (WLMs) are dynamic, self-assembling supramolecular structures that exhibit complex viscoelastic behaviour due to their ability to undergo reversible scission, fusion, branching, and sequence rearrangement. This review pro...

DOAJ Open Access (DOAJ) DOI: 10.3144/expresspolymlett.2026.36

Application of Artificial Neural Networks for Corrosion Behavior of Ni–Zn Electrophosphate Coating on Galvanized Steel and Gene Expression Programming Models

Malihe Zeraati, Hossein Abbasi, Parvin Ghaffarzadeh, Narendra Pal Singh Chauhan et al. • Frontiers in Materials (2022)

Zn–Ni electrophosphate coating is one of the most commonly used materials in industrial applications. The corrosion resistance of this coating is very important in order to achieve the minimum corrosion current of the Zn–Ni electrophosphate...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmats.2022.823155

Neural networks

Bernard Carlos Widrow, David E. Rumelhart, Michael A. Lehr • Communications of the ACM (1994)

article Free Access Share on Neural networks: applications in industry, business and science Authors: Bernard Widrow Stanford Univ., Stanford, CA Stanford Univ., Stanford, CAView Profile , David E. Rumelhart Stanford Univ., Stanford, CA Sta...

OPENALEX Open Access DOI: https://doi.org/10.1145/175247.175257

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

Machine learning in construction: From shallow to deep learning

Yayin Xu, Ying Zhou, Przemysław Sekuła, Lieyun Ding • Developments in the Built Environment (2021)

The development of artificial intelligence technology is currently bringing about new opportunities in construction. Machine learning is a major area of interest within the field of artificial intelligence, playing a pivotal role in the pro...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.dibe.2021.100045