Article
Agriculture, Multidisciplinary
Cicero Jorge Fonseca Dolacio, Veronica Satomi Kazama, Rafael Schmitz, Ana Paula Dalla Corte, Luiz Rodolfo Reis Costa, Maria de Nazare Martins Maciel
Summary: This study aimed to test whether adding soil chemical variables as secondary variables to ordinary kriging could improve the precision of simulating the volume of Brazilian-mahogany commercial wood. The exponential geostatistical model was found to be the best choice in all scenarios, but the models in scenario two were not good alternatives due to lack of strong spatial dependence. The approach in scenario three proved to be the best alternative for interpolating v(c), followed by scenario one.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Computer Science, Artificial Intelligence
Bardia Bayat, Mohsen Nasseri, Eric Delmelle
Summary: The paper develops a framework for rainfall network design that combines fuzzy concepts and a deterministic spatial interpolation method. Comparison of different fuzzy mathematical approaches shows that FM-IDW method yields better results, with statistical analysis revealing significant impact of number of removed stations on estimation accuracy.
APPLIED SOFT COMPUTING
(2021)
Article
Biochemistry & Molecular Biology
Toktam Bagheri, Ali Misaghi, Ali Taheri MirGhaed, Abolfazl Kamkar, Aliakbar Hedayati
Summary: This survey evaluated heavy metal accumulation in edible fishes from Gorgan Bay. Results showed that mullet from the estuary had the highest accumulation of arsenic, while roach from the mouth of the channel had the lowest contamination. The highest pollution of cadmium and copper was observed in fishes caught from the estuary. The study highlights the importance of limiting fishing times and locations to minimize heavy metal contamination in the ecologically sensitive Gorgan Bay.
BIOLOGICAL TRACE ELEMENT RESEARCH
(2023)
Article
Geosciences, Multidisciplinary
Ali Keshavarzi, Henry Oppong Tuffour, Eric C. Brevik, Gunes Ertunc
Summary: Understanding how topography affects soil properties is crucial in landscape management, this study used various interpolation techniques and fractal analysis to assess this impact. Elevation was found to be the most influential covariate in predicting soil properties. The results showed high accuracy in predicting soil property distribution maps, with short range spatial variability and weak correlations observed.
Article
Environmental Sciences
Toktam Bagheri, Ali Misaghi, Ali Taheri MirGhaed, Abolfazl Kamkar, Aliakbar Hedayati, Hessameddin Akbarein
Summary: Just recently, the presence of heavy metals in aquatic animals, particularly fishes, has been detected, leading to the need for a method to assess the health risks for humans who consume these contaminated fishes. The present study aimed to assess the health risk associated with the consumption of four heavy metals (arsenic, cadmium, lead, and copper) in three main edible fishes caught from Gorgan bay. The results indicate that the heavy metals found in Gorgan bay do not pose serious risks to consumer health, although there were some exceedances of acceptable values for target cancer risk.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Environmental Sciences
A. Karimkhani Bahador, S. Feiznia, M. Aleali, M. Arian
Summary: The study in the Southern Caspian Sea indicates that the environmental pollution in the area is mainly caused by the sediment loads carried by the Chalous, Sardabroud and Namak Abroud rivers. Heavy metal contamination is concentrated in river and shallow water sediments, which may be due to the use of pesticides and chemical fertilizers in agricultural lands.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY
(2021)
Article
Environmental Sciences
Farnaz Irandoost, Homira Agah, Zahra Eslami, Loreto Rossi, Francesco Colloca, Amir Khalili, Maria Letizia Costantini
Summary: The study conducted health risk assessment and ecological risk assessment on the pollution in the Caspian Sea, indicating that simultaneous use of physicochemical properties of water and heavy metal levels resulted in the best prediction of isotopic nitrogen content.
MARINE POLLUTION BULLETIN
(2021)
Article
Environmental Sciences
Yifan Wang, Ruimin Liu, Yuexi Miao, Lijun Jiao, Leiping Cao, Lin Li, Qingrui Wang
Summary: In different seasons, the high-risk areas of Cr, Cd, and Hg pollution in sediments of the Yangtze River estuary were relatively high, with Cr pollution being the most severe, while there were discrepancies between the OK and IK results.
MARINE POLLUTION BULLETIN
(2021)
Article
Ecology
Tian Gan, Hongwen Zhao, Yi Ai, Sihu Zhang, Yongli Wen, Liming Tian, Tserang Donko Mipam
Summary: Heavy metals elements not only affect ecosystems but also human health. The study found that only Cd and Pb exceeded their background values in the topsoil of the Zoige alpine basin, with Cd being 2.02- and 1.55-fold higher than its background value in May and September, respectively, and Pb being 2.35- and 2.17-fold higher than its background value in May and September, respectively. The comprehensive potential ecological risk index indicated low pollution levels in the study area. Spatial interpolation suggested that Cd and Pb pollution might be related to tourism and transportation, but the low biological absorption coefficient of heavy metals in forage indicated minimal impact on yak breeding. Overall, the soil in the basin was lightly contaminated with Cd and Pb due to rapid development in animal husbandry and tourism. Spatial variation of heavy metals was primarily influenced by structural factors, while random factors such as overgrazing influenced the content and distribution of soil heavy metals.
FRONTIERS IN ECOLOGY AND EVOLUTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Italo Gomes Goncalves, Felipe Guadagnin, Diogo Peixoto Cordova
Summary: This paper introduces a variational Gaussian process (VGP) model specialized in spatial data by leveraging recent advances in the machine learning field. The model is highly modular and customizable, allowing for different assumptions about the data. The focus of this work is on multivariate robust regression using an adaptation of the e-insensitive loss function. The VGP model enables end-to-end modeling with normal score transformation, spatial pattern detection, and prediction. The paper also presents a methodology for handling large datasets and provides an open-source implementation.
COMPUTERS & GEOSCIENCES
(2022)
Article
Environmental Sciences
Milad Adel, Chiara Copat, Gea Oliveri Conti, Fahimeh Sakhaie, Zahra Hashemi, Giuseppe Mancini, Antonio Cristaldi, Margherita Ferrante
Summary: This study aimed to analyze the levels of trace elements in two species of fish in the southwest of the Caspian Sea, and assess the potential risks to human health. The results showed that the Target Hazard Quotient (THQ) for both children and adults was below 1, indicating a relatively low risk associated with the consumption of these fish.
MARINE POLLUTION BULLETIN
(2022)
Article
Engineering, Marine
Riyadh F. Halawani, Myra E. Wilson, Kenneth M. Hamilton, Fahed A. Aloufi, Md Abu Taleb, Aaid G. Al-Zubieri, Andrew N. Quicksall
Summary: Coastal development in the Red Sea has led to increased levels of anthropogenic heavy metals in sediments, with the highest concentrations found in the Middle and South regions near Jeddah. Various indices were calculated to assess the pollution and enrichment of specific metals in different locations along the coastline.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Environmental Sciences
Samuel Kudjo Ahado, Chukwudi Nwaogu, Vincent Yaw Oppong Sarkodie, Lubos Boruvka
Summary: This study aimed to evaluate the concentrations and distribution of PTEs in soils from an industrialized region, as well as identify their possible sources. Analysis of 442 soil samples revealed high variability in PTEs in both organic and mineral soils. Despite low pollution levels in the area, periodic assessment of soil may be necessary to prevent future accumulation. This information could be valuable for policy-makers in promoting sustainable agriculture and forestry for ecosystem health and overall welfare.
Article
Environmental Sciences
Safaa Abdel Ghani, Samia Hamdona, Laila Shakweer, Abeer El Saharty
Summary: This study investigates the distribution of heavy metals in seawater along the eastern Egyptian Mediterranean Sea coast and evaluates the water quality. The results show that there is heavy metal pollution in Eastern Harbour, Abu-Qir, and Port Said sectors, and the pollution levels vary across seasons and regions.
MARINE POLLUTION BULLETIN
(2023)
Article
Chemistry, Multidisciplinary
Mohammed Al-Yaari, Theyazn H. H. Aldhyani, Sayeed Rushd
Summary: In this study, a new artificial neural network (ANN) model was developed using different architectures of an adaptive network-based fuzzy inference system (ANFIS) to predict the adsorption efficiency of arsenate (As(III)) from polluted water. The results showed that the ANFIS model had high prediction accuracy and identified the dominant factors affecting the adsorption process efficiency.
APPLIED SCIENCES-BASEL
(2022)
Article
Ecology
Mohsen Emadi-Tafti, Behzad Ataie-Ashtiani, Seiyed Mossa Hosseini
Summary: This study utilized an integrated 2D numerical model to examine the mechanical effects of vegetation and soil type on slope stability. The results showed that vegetation can prevent shallow landslides but has limited impact on deep landslides. The ratio of root zone depth to the depth of slide is a key parameter in enhancing slope stability through vegetation.
ECOLOGICAL MODELLING
(2021)
Article
Green & Sustainable Science & Technology
Esmaeel Parizi, Mehdi Bagheri-Gavkosh, Seiyed Mossa Hosseini, Fatemeh Geravand
Summary: This study analyzed the driving factors of flood peak discharges in Iran's basins using GIS, showing that drainage area, elevation, precipitation, slope, and NDVI are the main drivers of flood peaks at different frequencies. The results suggest that flood peak discharges increase with drainage area, heavy precipitation, and slope, while decreasing with elevation and NDVI across all study basins and frequencies.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Water Resources
Esmaeel Parizi, Seiyed Mossa Hosseini, Behzad Ataie-Ashtiani, Zahir Nikraftar
Summary: This study investigated the hydraulic interactions between Lake Urmia (LU) and the aquifers, providing a method to quantify this interaction. The results showed that the groundwater flux controls a significant portion of the lake's water storage. Understanding the hydraulic interaction between LU and the aquifers is crucial for sustainable management.
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
(2022)
Correction
Chemistry, Multidisciplinary
Asieh Sadat Kazemi, Ali Akbar Noroozi, Anousha Khamsavi, Ali Mazaheri, Seiyed Mossa Hosseini, Yaser Abdi
Article
Geosciences, Multidisciplinary
Shokoufeh Khojeh, Behzad Ataie-Ashtiani, Seiyed Mossa Hosseini
Summary: This study evaluated the efficiency of different Digital Elevation Models (DEMs) in simulating flood inundation areas. The results showed that ALOS and SRTM-30 m performed better in terms of accuracy, while ASTER showed the worst performance. These findings can be used as a basis for selecting DEM sources for flood inundation mapping.
Article
Engineering, Civil
Bahador Zarei, Esmaeel Parizi, Seiyed Mossa Hosseini, Behzad Ataie-Ashtiani
Summary: This study developed a groundwater sustainable management index that includes components of environmental, social, economic, and institutional responsibility. Four significant indicators were adopted and executed to evaluate 443 of Iran's aquifers. The results showed that 32% of Iran's aquifers have poor-very poor groundwater sustainable management, and the index is more sensitive to economic and social indicators. Additionally, there was an inverse correlation between the groundwater sustainable management index values and the coefficient of variation of the normalized difference vegetation index.
WATER INTERNATIONAL
(2022)
Article
Environmental Sciences
Esmaeel Parizi, Shokoufeh Khojeh, Seiyed Mossa Hosseini, Yaser Jouybari Moghadam
Summary: This study investigated the impact of UAV DEM resolution on flood characteristics and quantified the errors of global DEMs using UAV DEM measurements. The results showed that decreasing UAV DEM resolution led to an increase in inundation area and mean flow depth, while mean flow velocity decreased. The validation demonstrated that the HEC-RAS 2D model in conjunction with UAV DEM accurately simulated the flood. Comparing global DEMs, TDX DEM performed better, particularly in terms of inundation area.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Engineering, Civil
Seyed Mostafa Mousavi, Behzad Ataie-Ashtiani, Seiyed Mossa Hosseini
Summary: This study compared statistical approaches and multi-criteria-decision-making (MCDM) in flood hazard susceptibility mapping (FHSM) and evaluated their performance in a case study in northern Iran. The results showed that the MCDM approach outperformed statistical methods in predicting flood risk.
JOURNAL OF HYDROLOGY
(2022)
Article
Environmental Sciences
Fatemeh Geravand, Seiyed Mossa Hosseini, Mehran Maghsoudi, Mojtaba Yamani
Summary: This study focuses on the quantitative and qualitative characterization of karst aquifers in the Zagros Mountains region in western Iran. By using state-of-the-art statistical methods, the researchers analyzed spring recession hydrograph and spring water quality to gain insights into the karst aquifers. The results showed that these resources are crucial for the region and the majority of the studied aquifers have a high degree of karstification.
ENVIRONMENTAL EARTH SCIENCES
(2022)
Article
Environmental Sciences
Amir-Reza Sadeghi, Seiyed Mossa Hosseini
Summary: Demarcation of potentially favorable zones for groundwater artificial recharge (GAR) is crucial for preventing saltwater intrusion and ensuring sustainability of groundwater resources in arid regions. This study developed an overlay-index methodology using ArcGIS to delineate these zones based on 11 influential factors. The methodology was applied to two coastal aquifers in Central Iran, and the resulting GAR map showed high accuracy in identifying suitable areas for GAR. The study also estimated the water requirement for GAR to control seawater intrusion in these aquifers, providing valuable information for managers in arid regions.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2023)
Article
Engineering, Civil
Mehdi Bagheri-Gavkosh, Seiyed Mossa Hosseini
Summary: Flood seasonality analysis is crucial for identifying hydrologically homogenous regions and understanding flood risk in arid regions. This study analyzed the seasonality of annual maximum floods in 291 stations across Iran and examined the relationships between flood season and various factors. The findings showed strong seasonality in flooding, with a significant difference between northern and southeastern regions. The study suggests that the geographical location of the hydrometric station, particularly latitude, plays a more significant role in shaping flood seasonality.
JOURNAL OF HYDROLOGIC ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Seiyed Mossa Hosseini
Summary: This study investigated the use of a nonpumping reactive wells (NPRWs) system with a mixture of granular activated carbon (GAC) and microscale zero-valent iron (MZVI) for the treatment of nitrate-contaminated groundwater. Batch experiments were conducted to determine the reduction kinetics of nitrate and phosphate in water. The results showed that the GAC-based NPRWs achieved a 0.6% g(-1) reduction rate for nitrate, while the mixed MZVI/GAC achieved a higher efficiency of 5.5% g(-1). The use of mixed MZVI/GAC in NPRWs resulted in minimal changes in pH and EC of the groundwater outflows.
CLEAN-SOIL AIR WATER
(2023)
Article
Environmental Sciences
Sorour Sheibani, Behzad Ataie-Ashtiani, Ammar Safaie, Seiyed Mossa Hosseini
Summary: The dynamic evolution of storage volume and salinity of Lake Urmia was investigated. A coupled mathematical model considering the two-way effect of salt and water balance components was developed to estimate the groundwater flux. The results showed significant salt precipitation and decreased evaporation during the lake shrinkage period, while the rising water level resulted in salt dissolution and decreased salinity in the following years.
JOURNAL OF GREAT LAKES RESEARCH
(2023)
Article
Geosciences, Multidisciplinary
Zahir Nikraftar, Esmaeel Parizi, Mohsen Saber, Seiyed Mossa Hosseini, Behzad Ataie-Ashtiani, Craig T. Simmons
Summary: This study utilizes remote-sensing hydrological data and reanalyzed ERA5-Land data to conduct a comprehensive spatiotemporal and sustainability analysis of freshwater availability and wet/dry periods in the Middle East. The results reveal a significant decline in groundwater storage and highlight the unsustainable nature of the majority of basins in the region. These findings are crucial for mitigating drought risks in a region with limited ground-data sources.
HYDROGEOLOGY JOURNAL
(2023)
Article
Water Resources
Asal Golpaygani, Amirreza Keshtkar, Naser Mashhadi, Seiyed Mossa Hosseini, Ali Afzali
Summary: This study focuses on the Hablehrood River watershed in the northern part of the Iranian Central Plateau, aiming to find the most economical management scenarios for implementing biological best management practices (BMPs) to solve the runoff issue. The study uses SWAT and GA models to determine the best biological management practice with the highest runoff reduction and the lowest possible cost.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2023)
Review
Computer Science, Artificial Intelligence
Wei Gao, Shuangshuang Ge
Summary: This study provides a comprehensive review of slope stability research based on artificial intelligence methods, focusing on slope stability computation and evaluation. The review covers studies using quasi-physical intelligence methods, simulated evolutionary methods, swarm intelligence methods, hybrid intelligence methods, artificial neural network methods, vector machine methods, and other intelligence methods. The merits, demerits, and state-of-the-art research advancement of these studies are analyzed, and possible research directions for slope stability investigation based on artificial intelligence methods are suggested.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Khuong Le Nguyen, Hoa Thi Trinh, Saeed Banihashemi, Thong M. Pham
Summary: This study investigated the influence of input parameters on the shear strength of RC squat walls and found that ensemble learning models, particularly XGBoost, can effectively predict the shear strength. The axial load had a greater influence than reinforcement ratio, and longitudinal reinforcement had a more significant impact compared to horizontal and vertical reinforcement. The performance of XGBoost model outperforms traditional design models and reducing input features still yields reliable predictions.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Bo Hu, Huiyan Zhang, Xiaoyi Wang, Li Wang, Jiping Xu, Qian Sun, Zhiyao Zhao, Lei Zhang
Summary: A deep hierarchical echo state network (DHESN) is proposed to address the limitations of shallow coupled structures. By using transfer entropy, candidate variables with strong causal relationships are selected and a hierarchical reservoir structure is established to improve prediction accuracy. Simulation results demonstrate that DHESN performs well in predicting algal bloom.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Limin Wang, Lingling Li, Qilong Li, Kuo Li
Summary: This paper discusses the urgency of learning complex multivariate probability distributions due to the increase in data variability and quantity. It introduces a highly scalable classifier called TAN, which utilizes maximum weighted spanning tree (MWST) for graphical modeling. The paper theoretically proves the feasibility of extending one-dependence MWST to model high-dependence relationships and proposes a heuristic search strategy to improve the fitness of the extended topology to data. Experimental results demonstrate that this algorithm achieves a good bias-variance tradeoff and competitive classification performance compared to other high-dependence or ensemble learning algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhejing Hu, Gong Chen, Yan Liu, Xiao Ma, Nianhong Guan, Xiaoying Wang
Summary: Anxiety is a prevalent issue and music therapy has been found effective in reducing anxiety. To meet the diverse needs of individuals, a novel model called the spatio-temporal therapeutic music transfer model (StTMTM) is proposed.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Nur Ezlin Zamri, Mohd. Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, Siti Syatirah Sidik, Alyaa Alway, Nurul Atiqah Romli, Yueling Guo, Siti Zulaikha Mohd Jamaludin
Summary: In this study, a hybrid logic mining model was proposed by combining the logic mining approach with the Modified Niche Genetic Algorithm. This model improves the generalizability and storage capacity of the retrieved induced logic. Various modifications were made to address other issues. Experimental results demonstrate that the proposed model outperforms baseline methods in terms of accuracy, precision, specificity, and correlation coefficient.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys
Summary: The paper addresses the problem of efficiently optimizing machine learning solutions by reducing the configuration space of ML pipelines and leveraging historical performance. The experiments conducted show that opportunistic/systematic meta-knowledge can improve ML outcomes, and configuration-space culling is optimal when balanced. The utility and impact of meta-knowledge depend on various factors and are crucial for generating informative meta-knowledge bases.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
G. Sophia Jasmine, Rajasekaran Stanislaus, N. Manoj Kumar, Thangamuthu Logeswaran
Summary: In the context of a rapidly expanding electric vehicle market, this research investigates the ideal locations for EV charging stations and capacitors in power grids to enhance voltage stability and reduce power losses. A hybrid approach combining the Fire Hawk Optimizer and Spiking Neural Network is proposed, which shows promising results in improving system performance. The optimization approach has the potential to enhance the stability and efficiency of electric grids.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhijiang Wu, Guofeng Ma
Summary: This study proposes a natural language processing-based framework for requirement retrieval and document association, which can help to mine and retrieve documents related to project managers' requirements. The framework analyzes the ontology relevance and emotional preference of requirements. The results show that the framework performs well in terms of iterations and threshold, and there is a significant matching between the retrieved documents and the requirements, which has significant managerial implications for construction safety management.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Yung-Kuan Chan, Chuen-Horng Lin, Yuan-Rong Ben, Ching-Lin Wang, Shu-Chun Yang, Meng-Hsiun Tsai, Shyr-Shen Yu
Summary: This study proposes a novel method for dog identification using nose-print recognition, which can be applied to controlling stray dogs, locating lost pets, and pet insurance verification. The method achieves high recognition accuracy through two-stage segmentation and feature extraction using a genetic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Shaohua Song, Elena Tappia, Guang Song, Xianliang Shi, T. C. E. Cheng
Summary: This study aims to optimize supplier selection and demand allocation decisions for omni-channel retailers in order to achieve supply chain resilience. It proposes a two-phase approach that takes into account various factors such as supplier evaluation and demand allocation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jinyan Hu, Yanping Jiang
Summary: This paper examines the allocation problem of shared parking spaces considering parking unpunctuality and no-shows. It proposes an effective approach using sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm to solve the problem. The numerical experiments demonstrate the significance of supply-demand balance for the operation and user satisfaction of the shared parking system.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Soroor Motie, Bijan Raahemi
Summary: Financial fraud is a persistent problem in the finance industry, but Graph Neural Networks (GNNs) have emerged as a powerful tool for detecting fraudulent activities. This systematic review provides a comprehensive overview of the current state-of-the-art technologies in using GNNs for financial fraud detection, identifies gaps and limitations in existing research, and suggests potential directions for future research.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Enhao Ning, Changshuo Wang, Huang Zhang, Xin Ning, Prayag Tiwari
Summary: This review provides a detailed overview of occluded person re-identification methods and conducts a systematic analysis and comparison of existing deep learning-based approaches. It offers important theoretical and practical references for future research in the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jiajun Ma, Songyu Hu, Jianzhong Fu, Gui Chen
Summary: The article presents a novel visual hierarchical attention detector for multi-scale defect location and classification, utilizing texture, semantic, and instance features of defects through a hierarchical attention mechanism, achieving multi-scale defect detection in bearing images with complex backgrounds.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
