Improved sports image classification using deep neural network and novel tuna swarm optimization DOI Creative Commons

Zetian Zhou,

Heqing Zhang, Mehdi Effatparvar

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: June 19, 2024

Abstract Sports image classification is a complex undertaking that necessitates the utilization of precise and robust techniques to differentiate between various sports activities. This study introduces novel approach combines deep neural network (DNN) with modified metaheuristic algorithm known as tuna swarm optimization (NTSO) for purpose classification. The DNN potent technique capable extracting high-level features from raw images, while NTSO optimizes hyperparameters DNN, including number layers, neurons, activation functions. Through application finely-tuned developed, exhibiting exceptional performance in Rigorous experiments have been conducted on an extensive dataset obtained results compared against other state-of-the-art methods, Attention-based graph convolution-guided third-order hourglass (AGTH-Net), particle (PSO), YOLOv5 backbone SPD-Conv, Depth Learning (DL). According fivefold cross-validation technique, DNN/NTSO model provided remarkable precision, recall, F1-score results: 97.665 ± 0.352%, 95.400 0.374%, 0.8787 0.0031, respectively. Detailed comparisons reveal model's superiority toward metrics, solidifying its standing top choice tasks. Based practical dataset, has successfully evaluated real-world scenarios, showcasing resilience flexibility categories. Its capacity uphold precision dynamic settings, where elements like lighting, backdrop, motion blur are prominent, highlights utility. scalability efficiency analyzing images live competitions additionally validate suitability integration into real-time analytics media platforms. research not only confirms theoretical but also pragmatic effectiveness wide array demanding assignments.

Language: Английский

Application of Meta-Heuristic Algorithms for Training Neural Networks and Deep Learning Architectures: A Comprehensive Review DOI Open Access
Mehrdad Kaveh, Mohammad Saadi Mesgari

Neural Processing Letters, Journal Year: 2022, Volume and Issue: 55(4), P. 4519 - 4622

Published: Oct. 31, 2022

Language: Английский

Citations

131
Stretchable-thickness model for dynamic responses of graphene origami reinforced badminton sport plate DOI
Wenwen Wang, Jianhua Zhang, Mostafa Habibi

et al.

Mechanics of Advanced Materials and Structures, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 13

Published: July 8, 2024

In this article, we organize a stretchable-thickness model to present frequency analysis for composite plate applicable in badminton court which is reinforced with origami graphene. A higher order kinematic extended work including three bending, shear, and stretching functions, where the functions responsible satisfying out of plane shear strains stresses at top/bottom surfaces equipment. The sport or composites manufactured from copper matrix graphene effective material properties are calculated based on micromechanical models as function volume fraction folding degree origami, reinforcement temperature. numerical results presented changes fraction, reinforcement, thermal loading along thickness direction. main novelty accounting deformation investigating responses new reinforcement. verification investigation approve methodology, solution procedure. An various ratio plate.

Language: Английский

Citations

21
Application of a folded nanostructure reinforcement for the pole vault curved shell DOI

Song Zhi-qiang,

Li Aiyun,

Zhao Daichang

et al.

Mechanics of Advanced Materials and Structures, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 15

Published: July 8, 2024

Foldability capacity is now introduced as a novel nanofiller reinforcement production procedure using some operation to control the mechanical, thermal and electrical properties in sport equipment. Application of this type nanofillers curved structures like pole vault shell leads engineering shape structures. This article organized suggest vibration-based formulation for analysis folded reinforced structure subjected mechanical loading. Using computation kinetic, strain external energies, one can arrive motion's equations minimization total energy Hamilton's principle. solution through an analytical approach, parametric presented. The verified test presented confirmation trend results.

Language: Английский

Citations

21
Multi-load effect on the deformation analysis of composite nano reinforced origami sandwich panel DOI
Cizhen Yu, Peng Lin, Zhixin Wu

et al.

Mechanics of Advanced Materials and Structures, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 19

Published: June 19, 2024

Graphene origami in a copper matrix is used as composition of core sandwich panel between two piezoelectric/piezomagnetic layers. More accurate modeling the composite structure performed using higher-order model including thickness stretching term. Principle virtual work order to derive governing equations terms resultant components force and moment well electromagnetic loads. The are derived framework with accounting electric magnetic potentials effective material properties graphene Halpin-Tsai rule mixture framework. deformation/strain/stress analytically obtained thermal, mechanical, electrical, loads folding degree content origami. Verification for justification numerical results. A foldability dependent parametric analysis presented show controllability stress, strain deformations along direction.

Language: Английский

Citations

16
Predicting the environmental economic dispatch problem for reducing waste nonrenewable materials via an innovative constraint multi-objective Chimp Optimization Algorithm DOI
Lei Zhu, Hao Ren, Mostafa Habibi

et al.

Journal of Cleaner Production, Journal Year: 2022, Volume and Issue: 365, P. 132697 - 132697

Published: June 16, 2022

Language: Английский

Citations

47
Multi-Objective chimp Optimizer: An innovative algorithm for Multi-Objective problems DOI
Mohammad Khishe, N. Orouji, M. R. Mosavi

et al.

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 211, P. 118734 - 118734

Published: Sept. 5, 2022

Language: Английский

Citations

46
BO-ALLCNN: Bayesian-Based Optimized CNN for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Smear Images DOI Creative Commons
Ghada Atteia, Amel Ali Alhussan, Nagwan Abdel Samee

et al.

Sensors, Journal Year: 2022, Volume and Issue: 22(15), P. 5520 - 5520

Published: July 24, 2022

Acute lymphoblastic leukemia (ALL) is a deadly cancer characterized by aberrant accumulation of immature lymphocytes in the blood or bone marrow. Effective treatment ALL strongly associated with early diagnosis disease. Current practice for initial performed through manual evaluation stained smear microscopy images, which time-consuming and error-prone process. Deep learning-based human-centric biomedical has recently emerged as powerful tool assisting physicians making medical decisions. Therefore, numerous computer-aided diagnostic systems have been developed to autonomously identify images. In this study, new Bayesian-based optimized convolutional neural network (CNN) introduced detection microscopic To promote classification performance, architecture proposed CNN its hyperparameters are customized input data Bayesian optimization approach. The technique adopts an informed iterative procedure search hyperparameter space optimal set that minimizes objective error function. trained validated using hybrid dataset formed integrating two public datasets. Data augmentation adopted further supplement image boost performance. search-derived model recorded improved performance image-based on test set. findings study reveal superiority Bayesian-optimized over other deep learning models.

Language: Английский

Citations

43
The optimization of nodes clustering and multi-hop routing protocol using hierarchical chimp optimization for sustainable energy efficient underwater wireless sensor networks DOI

Shukun He,

Qinlin Li,

Mohammad Khishe

et al.

Wireless Networks, Journal Year: 2023, Volume and Issue: 30(1), P. 233 - 252

Published: Aug. 21, 2023

Language: Английский

Citations

28
Optimization of hybrid energy management system based on high-energy solid-state lithium batteries and reversible fuel cells DOI
Xue Li,

Minghai Li,

Mostafa Habibi

et al.

Energy, Journal Year: 2023, Volume and Issue: 283, P. 128454 - 128454

Published: July 25, 2023

Language: Английский

Citations

25
Enhancing Robot Path Planning through a Twin-Reinforced Chimp Optimization Algorithm and Evolutionary Programming Algorithm DOI Creative Commons
Yang Zhang,

Hu Zhang

IEEE Access, Journal Year: 2023, Volume and Issue: unknown, P. 1 - 1

Published: Nov. 30, 2023

The importance of efficient path planning (PP) cannot be overstated in the domain robots, as it involves utilization intelligent algorithms to determine optimal trajectory for robot navigate between two given points.The main target PP is potential trajectories operating a complex environment containing various obstacles.The implementation these movements should facilitate traversing without encountering any collisions, starting from its initial location and reaching intended destination.In order address challenges associated with PP, this study applies chimp optimization algorithm (CHOA) local searching (LS) technique evolutionary programming (EPA) enhance route discovered via collection LSs.In CHOA's tendency converge minima, new updating called twin-reinforced (TR) developed.In assess effectiveness TRCHOA, we conducted comparative analysis other widely used meta-heuristic that are typically employed solving problems.Additionally, included conventional probabilistic roadmap method (PRM) our evaluation.We evaluated performances on standardized set benchmark problems.Our findings indicate TRCHOA outperforms terms performance.The evaluation encompasses several key criteria, namely length, consistency scheduled paths, time complexity, rate success.The experiments provide evidence statistically significant value enhancements obtained through proposed method.The derived compelling capacity accurately most within specified test map.

Language: Английский

Citations

25