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Lightweight Road Image Segmentation Algorithm Based on Multi-Scale Feature Fusion for Blind Guiding Scenarios

SHA Yuyang, LU Jingtao, DU Haofan, ZHAI Xiaobing, MENG Weiyu, LIAN Xu, LUO Gang, LI Kefeng • Jisuanji gongcheng (2025)

Image segmentation is a crucial technology for environmental perception, and it is widely used in various scenarios such as autonomous driving and virtual reality. With the rapid development of technology, computer vision-based blind guidin...

DOAJ Open Access (DOAJ) DOI: 10.19678/j.issn.1000-3428.0068674

Soft–Hard Attention U-Net Model and Benchmark Dataset for Multiscale Image Shadow Removal

Eirini Cholopoulou, Dimitrios E. Diamantis, Dimitra-Christina C. Koutsiou, Dimitris K. Iakovidis • IEEE Access (2026)

Effective shadow removal is pivotal in enhancing visual image quality in applications such as computer vision and digital photography. During the last decades physics-based and machine learning methodologies have been proposed; however, mos...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2026.3728048

A Wilson–Cowan reservoir computer for interpretable spatiotemporal vision

Sharmarke A. Gabayre, Sergey Savel’ev, Varuna De Silva, Mindula Illeperuma et al. • Scientific Reports (2026)

Abstract We present a Wilson–Cowan reservoir computer (WC–RC) that treats a retinotopic excitatory–inhibitory neural field as a structured reservoir. Travelling waves and bounded oscillations provide an interpretable spatiotemporal basis, w...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-49359-5

Toward Automated Structural Design for Controlled Vibration Characteristics Using Topology Optimization and Computer Vision in Space Missions

Musaddiq Al Ali, Masatoshi Shimoda, Marc Naguib • Applied Sciences (2024)

This study explores the integration of computer vision with topology optimization for additive manufacturing, with a focus on maximizing eigenfrequency in a design domain. Utilizing custom-developed photogrammetry software, high-resolution ...

DOAJ Open Access (DOAJ) DOI: 10.3390/app14156786

Assessment of the possibility of machine learning for electronic equipment quality prediction

Anna S. Kolosova, Anna S. Kameneva, Georgii G. Chukov, Alexander Y. Nikiforov • Безопасность информационных технологий (2023)

The major algorithms and methods of machine learning are considered. A possibility of machine learning and neural network using for electronic equipment quality prediction is assessed. The paper provides examples of the successful applicati...

DOAJ Open Access (DOAJ) DOI: 10.26583/bit.2023.1.09

DAPS3D: Domain Adaptive Projective Segmentation of 3D LiDAR Point Clouds

Alexey A. Klokov, Di Un Pak, Aleksandr Khorin, Dmitry A. Yudin et al. • IEEE Access (2023)

LiDARs are one of the key sources of reliable environmental ranging information for autonomous vehicles. However, segmentation of 3D scene elements (roads, buildings, people, cars, etc.) based on LiDAR point clouds has limitations. On the o...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3298706

Intelligent Algorithm for Rock Core RQD Based on Object Detection and Image Segmentation to Suppress Noise and Vibration

Feng Xiong, Jintao Wang, Guohua Zhang, Xueming Shi et al. • Advances in Civil Engineering (2024)

In the construction of the civil engineering infrastructure, the noise and vibration are affected by the geological conditions, adopting specific construction techniques based on the geological conditions is of great significance in suppres...

DOAJ Open Access (DOAJ) DOI: 10.1155/2024/3599911

Euclid Quick Data Release (Q1)

Bazzanini L., Angora G., Bergamini P., Meneghetti M. et al. • Astronomy & Astrophysics (2026)

Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust a...

DOAJ Open Access (DOAJ) DOI: 10.1051/0004-6361/202557590

Neural networks in geophysical applications

Mirko van der Baan, Christian Jutten B • Geophysics (2000)

Abstract Neural networks are increasingly popular in geophysics. Because they are universal approximators, these tools can approximate any continuous function with an arbitrary precision. Hence, they may yield important contributions to fin...

OPENALEX DOI: https://doi.org/10.1190/1.1444797

Surrogate Modeling of the Electric Field in the End-Winding Region of Pumped-Storage Generator Stators Based on Deep Neural Networks

Chunxu Qin, Yiran Ma, Huijuan Liang, Zhifan Wang et al. • Modelling (2026)

The end-winding insulation structure of stator windings in pumped-storage generator units is complex, with pronounced electric field concentration under out-of-phase conditions, making them critical concerns in insulation design and conditi...

DOAJ Open Access (DOAJ) DOI: 10.3390/modelling7050190

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

Memristor-based neural networks

Andy Thomas • Journal of Physics D Applied Physics (2013)

The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent p...

OPENALEX Open Access DOI: https://doi.org/10.1088/0022-3727/46/9/093001