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1,496 Results Found

  • Article
  • Open Access
1 Citations
2,342 Views
17 Pages

18 November 2024

Hyperspectral image (HSI) reconstruction is a critical and indispensable step in spectral compressive imaging (CASSI) systems and directly affects our ability to capture high-quality images in dynamic environments. Recent research has increasingly fo...

  • Article
  • Open Access
19 Citations
4,549 Views
21 Pages

In recent years, UNet and its improved variants have become the main methods for medical image segmentation. Although these models have achieved excellent results in segmentation accuracy, their large number of network parameters and high computation...

  • Article
  • Open Access
2,502 Views
18 Pages

Using panel data on 99 Italian provinces in the period between 2005 and 2020, the research investigates the effects of fundamental economic factors on the home sales at the provincial level, in order to build a forecasting model using a non-linear ar...

  • Article
  • Open Access
1 Citations
2,137 Views
17 Pages

7 July 2023

In recommendation models, bias can distort the distribution of user-generated data, leading to inaccurate representation of user preferences. Failure to filter out biased data can result in significant learning errors, ultimately reducing the accurac...

  • Article
  • Open Access
3 Citations
1,921 Views
15 Pages

Improving MLP-Based Weakly Supervised Crowd-Counting Network via Scale Reasoning and Ranking

  • Ming Gao,
  • Mingfang Deng,
  • Huailin Zhao,
  • Yangjian Chen and
  • Yongqi Chen

MLP-based weakly supervised crowd counting approaches have made significant advancements over the past few years. However, owing to the limited datasets, the current MLP-based methods do not consider the problem of region-to-region dependency in the...

  • Article
  • Open Access
1,750 Views
17 Pages

Transportation infrastructure systems sit at the nexus of urban economic development and emission mitigation. The primary objective is to identify and quantify the key factors influencing CI, with a focus on both the conventional and emerging indicat...

  • Article
  • Open Access
14 Citations
2,247 Views
20 Pages

Proposing a High-Precision Petroleum Pipeline Monitoring System for Identifying the Type and Amount of Oil Products Using Extraction of Frequency Characteristics and a MLP Neural Network

  • Abdulilah Mohammad Mayet,
  • Karina Shamilyevna Nurgalieva,
  • Ali Awadh Al-Qahtani,
  • Igor M. Narozhnyy,
  • Hala H. Alhashim,
  • Ehsan Nazemi and
  • Ilya M. Indrupskiy

13 August 2022

Setting up pipelines in the oil industry is very costly and time consuming. For this reason, a pipe is usually used to transport various petroleum products, so it is very important to use an accurate and reliable control system to determine the type...

  • Article
  • Open Access
658 Views
18 Pages

11 October 2025

In many current assembly scenarios, efficient collaboration between humans and robots can improve collaborative efficiency and quality. However, the efficient arrangement of human–robot collaborative (HRC) tasks constitutes a significant challe...

  • Communication
  • Open Access
5 Citations
3,007 Views
10 Pages

10 April 2023

Millimeter wave (MMW) communication, noted for its merit of wide bandwidth and high-speed transmission, is also a competitive implementation of the Internet of Everything (IoE). In an always-connected world, mutual data transmission and localization...

  • Article
  • Open Access
41 Citations
6,172 Views
16 Pages

Prediction of Building’s Thermal Performance Using LSTM and MLP Neural Networks

  • Miguel Martínez Comesaña,
  • Lara Febrero-Garrido,
  • Francisco Troncoso-Pastoriza and
  • Javier Martínez-Torres

23 October 2020

Accurate prediction of building indoor temperatures and thermal demand is of great help to control and optimize the energy performance of a building. However, building thermal inertia and lag lead to complex nonlinear systems is difficult to model. I...

  • Article
  • Open Access
3 Citations
2,010 Views
25 Pages

31 May 2024

In the modern world, the evolution of the internet supports the automation of several tasks, such as communication, education, sports, etc. Conversely, it is prone to several types of attacks that disturb data transfer in the network. Efficient attac...

  • Article
  • Open Access
10 Citations
5,093 Views
18 Pages

BLDC Motors Sensorless Control Based on MLP Topology Neural Network

  • Guozhong Yao,
  • Jiayu Feng,
  • Guiyong Wang and
  • Shaojun Han

11 May 2023

In order to reduce the complexity of the brushless DC motor (BLDC)-control-system algorithm while improving the estimation performance of the rotor phase position and the speed of the sensorless motor, a neural network (ANN) control algorithm based o...

  • Article
  • Open Access
13 Citations
3,873 Views
24 Pages

21 September 2023

Inertial measurement unit (IMU) technology has gained popularity in human activity recognition (HAR) due to its ability to identify human activity by measuring acceleration, angular velocity, and magnetic flux in key body areas like the wrist and kne...

  • Article
  • Open Access
2 Citations
2,496 Views
30 Pages

27 June 2025

This paper presents the implementation of a vision system for a collaborative robot equipped with a web camera and a Python-based control algorithm for automated object-sorting tasks. The vision system aims to detect, classify, and manipulate objects...

  • Article
  • Open Access
1,018 Views
20 Pages

Detecting AI-Generated Network Traffic Using Transformer–MLP Ensemble

  • Byeongchan Kim,
  • Abhishek Chaudhary and
  • Sunoh Choi

22 October 2025

The rapid growth of generative artificial intelligence (AI) has enabled diverse applications but also introduced new attack techniques. Similar to deepfake media, generative AI can be exploited to create AI-generated traffic that evades existing intr...

  • Article
  • Open Access
11 Citations
4,039 Views
16 Pages

27 January 2022

The parameter extraction of device models is critically important for circuit simulation. The device models in the existing parameter extraction software are physics-based analytical models, or embedded Simulation program with integrated circuit emph...

  • Article
  • Open Access
5 Citations
2,750 Views
17 Pages

Estimation of 3D Permeability from Pore Network Models Constructed Using 2D Thin-Section Images in Sandstone Reservoirs

  • Chengfei Luo,
  • Huan Wan,
  • Jinding Chen,
  • Xiangsheng Huang,
  • Shuheng Cui,
  • Jungan Qin,
  • Zhuoyu Yan,
  • Dan Qiao and
  • Zhiqiang Shi

7 October 2023

Using thin-section images to estimate core permeability is an economical and less time-consuming method for reservoir evaluation, which is a goal that many petroleum developers aspire to achieve. Although three-dimensional (3D) pore volumes have been...

  • Article
  • Open Access
2 Citations
1,937 Views
14 Pages

28 September 2023

In a complex multiaquifer mine, discriminant approaches that have previously been presented cannot successfully locate water sources. With multiple processing layers, computing models may learn representations of data at various levels of abstraction...

  • Article
  • Open Access
1,224 Views
20 Pages

16 June 2025

Long-term shutdowns caused by ice formation on wind turbine blades can lead to significant power generation losses, a persistent issue for wind farm operators. The rapid acquisition of ice mass and thickness on blades under actual meteorological cond...

  • Article
  • Open Access
4 Citations
3,202 Views
20 Pages

1 May 2020

The prediction of a high-level cognitive function based on a proactive brain–machine interface (BMI) control edge device is an emerging technology for improving the quality of life for disabled people. However, maintaining the stability of mult...

  • Article
  • Open Access
2 Citations
1,731 Views
23 Pages

9 July 2024

High-quality printing is a longstanding objective in the printing and replication industry. However, the methods used to evaluate print quality suffer from subjectivity and multidimensionality, relying on personal preferences and subjective perceptio...

  • Article
  • Open Access
13 Citations
4,933 Views
25 Pages

6 November 2024

Kolmogorov–Arnold Networks (KANs) are a novel class of neural network architectures based on the Kolmogorov–Arnold representation theorem, which has demonstrated potential advantages in accuracy and interpretability over Multilayer Percep...

  • Article
  • Open Access
1 Citations
922 Views
13 Pages

20 February 2025

This study evaluates the mapping accuracy between textile stretch sensor data and surface electromyography (sEMG) signals using Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), and Residual Network (ResNet) models. Data from the forea...

  • Feature Paper
  • Article
  • Open Access
24 Citations
6,803 Views
37 Pages

Improvement of Marine Steam Turbine Conventional Exergy Analysis by Neural Network Application

  • Sandi Baressi Šegota,
  • Ivan Lorencin,
  • Nikola Anđelić,
  • Vedran Mrzljak and
  • Zlatan Car

5 November 2020

This article presented an improvement of marine steam turbine conventional exergy analysis by application of neural networks. The conventional exergy analysis requires numerous measurements in seven different turbine operating points at each load, wh...

  • Article
  • Open Access
30 Citations
25,779 Views
22 Pages

LSTM–Transformer-Based Robust Hybrid Deep Learning Model for Financial Time Series Forecasting

  • Md R. Kabir,
  • Dipayan Bhadra,
  • Moinul Ridoy and
  • Mariofanna Milanova

10 January 2025

The inherent challenges of financial time series forecasting demand advanced modeling techniques for reliable predictions. Effective financial time series forecasting is crucial for financial risk management and the formulation of investment decision...

  • Article
  • Open Access
23 Citations
4,698 Views
18 Pages

Back to Basics: The Power of the Multilayer Perceptron in Financial Time Series Forecasting

  • Ana Lazcano,
  • Miguel A. Jaramillo-Morán and
  • Julio E. Sandubete

20 June 2024

The economic time series prediction literature has seen an increase in research leveraging artificial neural networks (ANNs), particularly the multilayer perceptron (MLP) and, more recently, transformer networks. These ANN models have shown superior...

  • Article
  • Open Access
72 Citations
8,749 Views
27 Pages

Development of a Multilayer Perceptron Neural Network for Optimal Predictive Modeling in Urban Microcellular Radio Environments

  • Joseph Isabona,
  • Agbotiname Lucky Imoize,
  • Stephen Ojo,
  • Olukayode Karunwi,
  • Yongsung Kim,
  • Cheng-Chi Lee and
  • Chun-Ta Li

3 June 2022

Modern cellular communication networks are already being perturbed by large and steadily increasing mobile subscribers in high demand for better service quality. To constantly and reliably deploy and optimally manage such mobile cellular networks, th...

  • Technical Note
  • Open Access
17 Citations
4,851 Views
15 Pages

Removing InSAR Topography-Dependent Atmospheric Effect Based on Deep Learning

  • Chen Chen,
  • Keren Dai,
  • Xiaochuan Tang,
  • Jianhua Cheng,
  • Saied Pirasteh,
  • Mingtang Wu,
  • Xianlin Shi,
  • Hao Zhou and
  • Zhenhong Li

25 August 2022

Atmospheric effects are among the primary error sources affecting the accuracy of interferometric synthetic aperture radar (InSAR). The topography-dependent atmospheric effect is particularly noteworthy in reservoir areas for landslide monitoring uti...

  • Article
  • Open Access
82 Citations
8,120 Views
20 Pages

Optimized Neural Architecture for Automatic Landslide Detection from High‐Resolution Airborne Laser Scanning Data

  • Mustafa Ridha Mezaal,
  • Biswajeet Pradhan,
  • Maher Ibrahim Sameen,
  • Helmi Zulhaidi Mohd Shafri and
  • Zainuddin Md Yusoff

16 July 2017

An accurate inventory map is a prerequisite for the analysis of landslide susceptibility, hazard, and risk. Field survey, optical remote sensing, and synthetic aperture radar techniques are traditional techniques for landslide detection in tropical r...

  • Article
  • Open Access
7 Citations
3,316 Views
26 Pages

8 August 2024

The vision transformer (ViT) has demonstrated performance comparable to that of convolutional neural networks (CNN) in the hyperspectral image classification domain. This is achieved by transforming images into sequence data and mining global spectra...

  • Article
  • Open Access
51 Citations
5,808 Views
17 Pages

How to Learn More? Exploring Kolmogorov–Arnold Networks for Hyperspectral Image Classification

  • Ali Jamali,
  • Swalpa Kumar Roy,
  • Danfeng Hong,
  • Bing Lu and
  • Pedram Ghamisi

29 October 2024

Convolutional neural networks (CNNs) and vision transformers (ViTs) have shown excellent capability in complex hyperspectral image (HSI) classification. However, these models require a significant number of training data and are computational resourc...

  • Article
  • Open Access
1 Citations
1,675 Views
13 Pages

Neural Network for Sky Darkness Level Prediction in Rural Areas

  • Alejandro Martínez-Martín,
  • Miguel Ángel Jaramillo-Morán,
  • Diego Carmona-Fernández,
  • Manuel Calderón-Godoy and
  • Juan Félix González González

6 September 2024

A neural network was developed using the Multilayer Perceptron (MLP) model to predict the darkness value of the night sky in rural areas. For data collection, a photometer was placed in three different rural locations in the province of Cácere...

  • Communication
  • Open Access
7 Citations
2,469 Views
17 Pages

Soft Computing Techniques for Appraisal of Potentially Toxic Elements from Jalandhar (Punjab), India

  • Vinod Kumar,
  • Parveen Sihag,
  • Ali Keshavarzi,
  • Shevita Pandita and
  • Andrés Rodríguez-Seijo

9 September 2021

The contamination of potentially toxic elements (PTEs) in agricultural soils is a serious concern around the globe, and modelling approaches is imperative in order to determine the possible hazards linked with PTEs. These techniques accurately assess...

  • Article
  • Open Access
12 Citations
2,058 Views
23 Pages

Loading Frequency Classification in Shape Memory Alloys: A Machine Learning Approach

  • Dmytro Tymoshchuk,
  • Oleh Yasniy,
  • Pavlo Maruschak,
  • Volodymyr Iasnii and
  • Iryna Didych

14 December 2024

This paper investigates the use of machine learning methods to predict the loading frequency of shape memory alloys (SMAs) based on experimental data. SMAs, in particular nickel-titanium (NiTi) alloys, have unique properties that restore the original...

  • Article
  • Open Access
6 Citations
2,545 Views
14 Pages

Modelling the Interaction between Air Pollutant Emissions and Their Key Sources in Poland

  • Alicja Kolasa-Więcek,
  • Dariusz Suszanowicz,
  • Agnieszka A. Pilarska and
  • Krzysztof Pilarski

20 October 2021

The main purpose of this study is to investigate the relationships between key sources of air pollutant emissions (sources of energy production, factories which are particularly harmful to the environment, the fleets of cars, environmental protection...

  • Article
  • Open Access
7 Citations
4,826 Views
17 Pages

29 August 2023

The classification of the United Nations Educational, Scientific, and Cultural Organization (UNESCO) World Heritage Sites (WHS) is essential for promoting sustainable tourism and ensuring the long-term conservation of cultural and natural heritage si...

  • Article
  • Open Access
4 Citations
1,896 Views
27 Pages

Background/Objective: Alzheimer’s disease is a progressive brain syndrome causing cognitive decline and, ultimately, death. Early diagnosis is essential for timely medical intervention, with MRI medical imaging serving as a primary diagnostic t...

  • Article
  • Open Access
30 Citations
4,422 Views
14 Pages

22 October 2020

The accurate prediction of the solar diffuse fraction (DF), sometimes called the diffuse ratio, is an important topic for solar energy research. In the present study, the current state of Diffuse irradiance research is discussed and then three robust...

  • Article
  • Open Access
20 Citations
8,823 Views
10 Pages

Development of an in Silico Model of DPPH• Free Radical Scavenging Capacity: Prediction of Antioxidant Activity of Coumarin Type Compounds

  • Elizabeth Goya Jorge,
  • Anita Maria Rayar,
  • Stephen J. Barigye,
  • María Elisa Jorge Rodríguez and
  • Maité Sylla-Iyarreta Veitía

A quantitative structure-activity relationship (QSAR) study of the 2,2-diphenyl-l-picrylhydrazyl (DPPH•) radical scavenging ability of 1373 chemical compounds, using DRAGON molecular descriptors (MD) and the neural network technique, a technique base...

  • Article
  • Open Access
2 Citations
2,914 Views
24 Pages

Real-Time Mobile Application for Translating Portuguese Sign Language to Text Using Machine Learning

  • Gonçalo Fonseca,
  • Gonçalo Marques,
  • Pedro Albuquerque Santos and
  • Rui Jesus

Communication barriers between deaf and hearing individuals present significant challenges to social inclusion, highlighting the need for effective technological aids. This study aimed to bridge this gap by developing a mobile system for the real-tim...

  • Article
  • Open Access
872 Views
34 Pages

2 December 2025

Reliable navigation in cooperative unmanned aerial vehicle (UAV) networks requires adaptively managing measurement degradations within Kalman-filter-based estimation frameworks. This paper introduces a learning-based Kalman approach for real-time det...

  • Article
  • Open Access
42 Citations
4,517 Views
15 Pages

24 June 2022

The aim of the study was to investigate the utility of artificial neural networks (ANNs) for the estimation of reference evapotranspiration (ETo) on the Peloponnese Peninsula in Greece for two representative months of wintertime and summertime during...

  • Article
  • Open Access
13 Citations
4,078 Views
14 Pages

Insight into the Structure–Odor Relationship of Molecules: A Computational Study Based on Deep Learning

  • Weichen Bo,
  • Yuandong Yu,
  • Ran He,
  • Dongya Qin,
  • Xin Zheng,
  • Yue Wang,
  • Botian Ding and
  • Guizhao Liang

9 July 2022

Molecules with pleasant odors, unacceptable odors, and even serious toxicity are closely related to human social life. It is impractical to identify the odors of molecules in large quantities (particularly hazardous odors) using experimental methods....

  • Article
  • Open Access
21 Citations
6,084 Views
26 Pages

RSS-Based Wireless LAN Indoor Localization and Tracking Using Deep Architectures

  • Muhammed Zahid Karakusak,
  • Hasan Kivrak,
  • Hasan Fehmi Ates and
  • Mehmet Kemal Ozdemir

Wireless Local Area Network (WLAN) positioning is a challenging task indoors due to environmental constraints and the unpredictable behavior of signal propagation, even at a fixed location. The aim of this work is to develop deep learning-based appro...

  • Article
  • Open Access
2 Citations
1,894 Views
18 Pages

Research on Earthquake Data Prediction Method Based on DIN–MLP Algorithm

  • Zhaoliang An,
  • Guannan Si,
  • Pengxin Tian,
  • Jianxin Li,
  • Xinyu Liang,
  • Fengyu Zhou and
  • Xiaoliang Wang

20 August 2023

This paper proposes a recommendation algorithm that combines MLP with the DIN model and conducts simulation experiments in the field of earthquake missing data prediction. The original DIN model may face challenges and weaknesses in earthquake monito...

  • Article
  • Open Access
4 Citations
2,279 Views
20 Pages

Methodology for the Prediction of the Thermal Conductivity of Concrete by Using Neural Networks

  • Ana Carolina Rosa,
  • Youssef Elomari,
  • Alejandro Calderón,
  • Carles Mateu,
  • Assed Haddad and
  • Dieter Boer

28 August 2024

The energy consumption of buildings presents a significant concern, which has led to a demand for materials with better thermal performance. Thermal conductivity (TC), among the most relevant thermal properties, is essential to address this demand. T...

  • Article
  • Open Access
183 Citations
23,198 Views
13 Pages

7 March 2019

The rapid, recent development of image recognition technologies has led to the widespread use of convolutional neural networks (CNNs) in automated image classification and in the recognition of plant diseases. Aims: The aim of the present study was t...

  • Article
  • Open Access
26 Citations
4,955 Views
16 Pages

4 November 2019

The grain handling industry plays a significant role in U.S. agriculture by storing, distributing, and processing a variety of agricultural commodities. Commercial grain elevators are hazardous agro-manufacturing work environments where workers are p...

  • Article
  • Open Access
3 Citations
2,365 Views
15 Pages

A Novel Three-Dimensional Reconstruction Technology for the Defect Inspection of Tubing and Casing

  • Zhiqiang Huang,
  • Xiaoliang Bai,
  • Zhi Yu,
  • Zhen Chen,
  • Na Feng,
  • Yufeng Ai,
  • Shigang Song and
  • Lili Xue

20 July 2023

The three-dimensional reconstruction of high-gloss/reflection and low-texture objects (e.g., oil casing threads) is a complex task. In this paper, we present a novel approach that combines convolutional neural networks (CNNs) and multi-layer percepti...

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