Analysis and design of optimal deep neural network model for image recognition using hybrid cuckoo search with self-adaptive particle swarm intelligence
Image recognition involves identifying objects in digital photos via computer algorithms and machine learning. Integrating cooperative behaviours and adaptive dynamics, bio-inspired swarm intelligence optimizes multiple algorithms for efficient solutions to complex challenges. CSO and SaPSO is combi...
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| Vydáno v: | Signal, image and video processing Ročník 18; číslo 10; s. 6987 - 6995 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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London
Springer London
01.09.2024
Springer Nature B.V |
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| ISSN: | 1863-1703, 1863-1711 |
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| Abstract | Image recognition involves identifying objects in digital photos via computer algorithms and machine learning. Integrating cooperative behaviours and adaptive dynamics, bio-inspired swarm intelligence optimizes multiple algorithms for efficient solutions to complex challenges. CSO and SaPSO is combined in this framework for enhanced optimization efficiency, promising faster convergence and better solutions. Employing Deep Convolution Generative Adversarial Networks (DC-GAN) for classification, the study achieves an outstanding 99.5% accuracy using Python. Through feature extraction, accuracy reaches 99%, indicating precise classification with minimal error. Key terms: DNN, Image Recognition, Bio-Inspired Swarm Intelligence, Hybrid Cuckoo Search, Self-Adaptive Particle Swarm Intelligence. |
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| AbstractList | Image recognition involves identifying objects in digital photos via computer algorithms and machine learning. Integrating cooperative behaviours and adaptive dynamics, bio-inspired swarm intelligence optimizes multiple algorithms for efficient solutions to complex challenges. CSO and SaPSO is combined in this framework for enhanced optimization efficiency, promising faster convergence and better solutions. Employing Deep Convolution Generative Adversarial Networks (DC-GAN) for classification, the study achieves an outstanding 99.5% accuracy using Python. Through feature extraction, accuracy reaches 99%, indicating precise classification with minimal error. Key terms: DNN, Image Recognition, Bio-Inspired Swarm Intelligence, Hybrid Cuckoo Search, Self-Adaptive Particle Swarm Intelligence. |
| Author | Kulkarni, Raj Shelar, Alankar |
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| Cites_doi | 10.1016/j.agwat.2022.107638 10.1007/s11042-022-12168-9 10.3390/biomimetics7020069 10.1007/s00500-023-08449-6 10.1007/s00521-022-07836-8 10.3390/s23073714 10.1016/j.future.2022.05.016 10.3390/s22103910 10.1016/j.crfs.2022.02.006 10.1007/s11042-023-15861-5 10.1007/s10846-022-01690-5 10.1038/s41598-020-59215-9 10.1016/j.energy.2021.120100 10.1007/s42235-022-00253-6 10.1007/s00521-020-05362-z 10.1007/s00366-020-01137-1 10.1007/s11042-022-12492-0 10.1007/s11633-022-1367-7 10.30684/etj.v38i2A.319 10.20517/ir.2021.08 |
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| Keywords | Deep neural network Image recognition Self-adaptive particle swarm intelligence Hybrid cuckoo search Bio-inspired swarm intelligence |
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| References | Kumar, Jayraj (CR19) 2023; 101 Dayana, Emmanuel (CR16) 2022; 81 Vijh, Saraswat, Kumar (CR18) 2023; 82 Sahlol, Kollmannsberger, Ewees (CR15) 2023; 10 Dayana, Emmanuel (CR14) 2023; 81 Fang, Liang (CR21) 2023; 20 Akkar, Salman (CR12) 2023; 38 Chatterjee, Saha, Sen, Oliva, Sarkar (CR25) 2023; 83 Subbiah, Chinnappan (CR6) 2022 Mafarja, Thaher, Too, Chantar, Turabieh, Houssein, Emam (CR23) 2023; 35 Zafar, Hussain, Ali, Lee (CR24) 2023; 23 Mangalampalli, Kumar (CR3) 2022; 135 Singh, Khanna, Garg, Singh (CR22) 2023; 28 CR4 Sajith, Srinivas, Golberg, Magner (CR7) 2022; 269 Vijh, Saraswat, Kumar (CR20) 2023; 82 Kondoyanni, Loukatos, Maraveas, Drosos, Arvanitis (CR9) 2022; 7 Zhang, Ali, Aldlemy, Mussa, Salih, Hameed, Al-Khafaji, Yaseen (CR17) 2023; 38 Kumar, Kumar, Kashyap, Aggarwal, Rathore, Kaiwartya, Lloret (CR5) 2022; 22 Chou, Truong, Kuo (CR13) 2023; 224 Wang, Cheng, Xia, Jiang (CR1) 2023; 20 Longa, Tsourdos, Inalhan (CR10) 2022; 105 Vijh, Gaurav, Pandey (CR11) 2023; 35 Khan, Shahrior, Karim, Hasan, Rahman (CR2) 2022; 34 Sarkar, Salauddin, Mukherjee, Shariati, Rebezov, Tretyak, Pateiro, Lorenzo (CR8) 2022; 5 JS Chou (3368_CR13) 2023; 224 A Zafar (3368_CR24) 2023; 23 A Mangalampalli (3368_CR3) 2022; 135 AM Dayana (3368_CR14) 2023; 81 AT Sahlol (3368_CR15) 2023; 10 GY Wang (3368_CR1) 2023; 20 AM Dayana (3368_CR16) 2022; 81 G Sajith (3368_CR7) 2022; 269 S Chatterjee (3368_CR25) 2023; 83 S Vijh (3368_CR18) 2023; 82 SS Subbiah (3368_CR6) 2022 M Mafarja (3368_CR23) 2023; 35 SI Khan (3368_CR2) 2022; 34 3368_CR4 T Sarkar (3368_CR8) 2022; 5 ME Longa (3368_CR10) 2022; 105 S Vijh (3368_CR20) 2023; 82 G Zhang (3368_CR17) 2023; 38 BS Kumar (3368_CR19) 2023; 101 LK Singh (3368_CR22) 2023; 28 M Kondoyanni (3368_CR9) 2022; 7 HA Akkar (3368_CR12) 2023; 38 L Fang (3368_CR21) 2023; 20 S Vijh (3368_CR11) 2023; 35 M Kumar (3368_CR5) 2022; 22 |
| References_xml | – volume: 269 year: 2022 ident: CR7 article-title: Bio-inspired and artificial intelligence-enabled hydro-economic model for diversified agricultural management publication-title: Agric. Water Manag. doi: 10.1016/j.agwat.2022.107638 – volume: 82 start-page: 4979 issue: 4 year: 2023 end-page: 5010 ident: CR20 article-title: Automatic multilevel image thresholding segmentation using hybrid bio-inspired algorithm and artificial neural network for histopathology images publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-022-12168-9 – volume: 82 start-page: 4979 issue: 4 year: 2023 end-page: 5010 ident: CR18 article-title: Automatic multilevel image thresholding segmentation using the hybrid bio-inspired algorithm and artificial neural network for histopathology images publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-022-12168-9 – ident: CR4 – volume: 7 start-page: 69 issue: 2 year: 2022 ident: CR9 article-title: Bio-inspired robots and structures toward fostering the modernization of agriculture publication-title: Biomimetics doi: 10.3390/biomimetics7020069 – volume: 28 start-page: 2431 issue: 3 year: 2023 end-page: 2467 ident: CR22 article-title: Emperor penguin optimization algorithm-and bacterial foraging optimization algorithm-based novel feature selection approach for glaucoma classification from fundus images publication-title: Soft. Comput. doi: 10.1007/s00500-023-08449-6 – volume: 35 start-page: 1749 issue: 2 year: 2023 end-page: 1775 ident: CR23 article-title: An efficient high-dimensional feature selection approach driven by enhanced multi-strategy grey wolf optimizer for biological data classification publication-title: Neural Comput. Appl. doi: 10.1007/s00521-022-07836-8 – volume: 23 start-page: 3714 issue: 7 year: 2023 ident: CR24 article-title: Metaheuristic optimization-based feature selection for imagery and arithmetic tasks: an fNIRS study publication-title: Sensors doi: 10.3390/s23073714 – volume: 135 start-page: 438 year: 2022 end-page: 449 ident: CR3 article-title: WBATimeNet: a deep neural network approach for VM live migration in the cloud publication-title: Futur. Gener. Comput. Syst. doi: 10.1016/j.future.2022.05.016 – volume: 22 start-page: 3910 issue: 10 year: 2022 ident: CR5 article-title: Green communication in the Internet of things: a hybrid bio-inspired intelligent approach publication-title: Sensors doi: 10.3390/s22103910 – volume: 5 start-page: 432 year: 2022 end-page: 450 ident: CR8 article-title: Application of bio-inspired optimization algorithms in food processing publication-title: Curr. Res. Food Sci. doi: 10.1016/j.crfs.2022.02.006 – volume: 101 start-page: 1817 issue: 4 year: 2023 end-page: 3195 ident: CR19 article-title: Resilient artificial fish swarm optimization-based enhanced convolutional neural network for autism spectrum disorder classification publication-title: J. Theor. Appl. Inf. Technol. – start-page: 169 year: 2022 end-page: 192 ident: CR6 publication-title: A review of bio-inspired computational intelligence algorithms in electricity load forecasting. Smart buildings digitalization – volume: 34 start-page: 6217 issue: 8 year: 2022 end-page: 6228 ident: CR2 article-title: MultiNet: a deep neural network approach for detecting breast cancer through multi-scale feature fusion publication-title: J. King Saud Univ.-Comput. Inf. Sci. – volume: 83 start-page: 11299 issue: 4 year: 2023 end-page: 11322 ident: CR25 article-title: Moth-flame optimization based deep feature selection for facial expression recognition using thermal images publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-023-15861-5 – volume: 105 start-page: 88 issue: 4 year: 2022 ident: CR10 article-title: Human–machine network through bio-inspired decentralized swarm intelligence and heterogeneous teaming in SAR operations publication-title: J. Intell. Rob. Syst. doi: 10.1007/s10846-022-01690-5 – volume: 10 start-page: 2536 issue: 1 year: 2023 ident: CR15 article-title: Efficient classification of white blood cell leukaemia with improved swarm optimization of deep features publication-title: Sci. Rep. doi: 10.1038/s41598-020-59215-9 – volume: 224 year: 2023 ident: CR13 article-title: Imaging time series with features to enable visual recognition of regional energy consumption by bio-inspired optimization of deep learning publication-title: Energy doi: 10.1016/j.energy.2021.120100 – volume: 20 start-page: 237 issue: 1 year: 2023 end-page: 252 ident: CR21 article-title: A novel method based on nonlinear binary grasshopper whale optimization algorithm for feature selection publication-title: J. Bionic Eng. doi: 10.1007/s42235-022-00253-6 – volume: 35 start-page: 23711 issue: 33 year: 2023 end-page: 23724 ident: CR11 article-title: Hybrid bio-inspired algorithm and convolutional neural network for automatic lung tumour detection publication-title: Neural Comput. Appl. doi: 10.1007/s00521-020-05362-z – volume: 38 start-page: 15 year: 2023 end-page: 28 ident: CR17 article-title: Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model publication-title: Eng. Comput. doi: 10.1007/s00366-020-01137-1 – volume: 81 start-page: 20611 issue: 15 year: 2022 end-page: 20642 ident: CR16 article-title: An enhanced swarm optimization-based deep neural network for diabetic retinopathy classification in fundus images publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-022-12492-0 – volume: 81 start-page: 20611 issue: 15 year: 2023 end-page: 20642 ident: CR14 article-title: An enhanced swarm optimization-based deep neural network for diabetic retinopathy classification in fundus images publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-022-12492-0 – volume: 20 start-page: 121 issue: 1 year: 2023 end-page: 144 ident: CR1 article-title: Swarm intelligence research: from bio-inspired single-population swarm intelligence to human-machine hybrid swarm intelligence publication-title: Mach. Intell. Res. doi: 10.1007/s11633-022-1367-7 – volume: 38 start-page: 255 issue: 2 year: 2023 end-page: 264 ident: CR12 article-title: Detection of biomedical images by using bio-inspired artificial intelligence publication-title: Eng. Technol. J. doi: 10.30684/etj.v38i2A.319 – volume: 38 start-page: 15 year: 2023 ident: 3368_CR17 publication-title: Eng. Comput. doi: 10.1007/s00366-020-01137-1 – volume: 224 year: 2023 ident: 3368_CR13 publication-title: Energy doi: 10.1016/j.energy.2021.120100 – ident: 3368_CR4 doi: 10.20517/ir.2021.08 – volume: 22 start-page: 3910 issue: 10 year: 2022 ident: 3368_CR5 publication-title: Sensors doi: 10.3390/s22103910 – volume: 135 start-page: 438 year: 2022 ident: 3368_CR3 publication-title: Futur. Gener. Comput. Syst. doi: 10.1016/j.future.2022.05.016 – volume: 105 start-page: 88 issue: 4 year: 2022 ident: 3368_CR10 publication-title: J. Intell. Rob. Syst. doi: 10.1007/s10846-022-01690-5 – volume: 269 year: 2022 ident: 3368_CR7 publication-title: Agric. Water Manag. doi: 10.1016/j.agwat.2022.107638 – volume: 34 start-page: 6217 issue: 8 year: 2022 ident: 3368_CR2 publication-title: J. King Saud Univ.-Comput. Inf. Sci. – volume: 28 start-page: 2431 issue: 3 year: 2023 ident: 3368_CR22 publication-title: Soft. Comput. doi: 10.1007/s00500-023-08449-6 – volume: 101 start-page: 1817 issue: 4 year: 2023 ident: 3368_CR19 publication-title: J. Theor. Appl. Inf. Technol. – volume: 82 start-page: 4979 issue: 4 year: 2023 ident: 3368_CR18 publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-022-12168-9 – volume: 35 start-page: 1749 issue: 2 year: 2023 ident: 3368_CR23 publication-title: Neural Comput. Appl. doi: 10.1007/s00521-022-07836-8 – volume: 38 start-page: 255 issue: 2 year: 2023 ident: 3368_CR12 publication-title: Eng. Technol. J. doi: 10.30684/etj.v38i2A.319 – volume: 82 start-page: 4979 issue: 4 year: 2023 ident: 3368_CR20 publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-022-12168-9 – volume: 35 start-page: 23711 issue: 33 year: 2023 ident: 3368_CR11 publication-title: Neural Comput. Appl. doi: 10.1007/s00521-020-05362-z – volume: 7 start-page: 69 issue: 2 year: 2022 ident: 3368_CR9 publication-title: Biomimetics doi: 10.3390/biomimetics7020069 – volume: 20 start-page: 237 issue: 1 year: 2023 ident: 3368_CR21 publication-title: J. Bionic Eng. doi: 10.1007/s42235-022-00253-6 – volume: 5 start-page: 432 year: 2022 ident: 3368_CR8 publication-title: Curr. Res. Food Sci. doi: 10.1016/j.crfs.2022.02.006 – volume: 23 start-page: 3714 issue: 7 year: 2023 ident: 3368_CR24 publication-title: Sensors doi: 10.3390/s23073714 – volume: 81 start-page: 20611 issue: 15 year: 2022 ident: 3368_CR16 publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-022-12492-0 – start-page: 169 volume-title: A review of bio-inspired computational intelligence algorithms in electricity load forecasting. Smart buildings digitalization year: 2022 ident: 3368_CR6 – volume: 10 start-page: 2536 issue: 1 year: 2023 ident: 3368_CR15 publication-title: Sci. 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| Title | Analysis and design of optimal deep neural network model for image recognition using hybrid cuckoo search with self-adaptive particle swarm intelligence |
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