Image segmentation for pest detection of crop leaves by improvement of regional convolutional neural network

Mohd Hanafiah, K. et al. Impact of Malaysian palm oil on sustainable development goals: co-benefits and trade-offs across mitigation strategies. Sustain. Sci. 17, 1639–1661 (2022).Article 
PubMed 

Google Scholar 
Pal, S., Samanta, S. & Banerjee, A. Seasonal incidence of pulse aphid (Aphis craccivora Koch.) and its natural enemies on field pea (Pisum sativum L.) in relation to some abiotic factors in Alluvial Zone of West Bengal. Legume Res. 46, 1680–1685 (2023).
Google Scholar 
Kalpna, Hajam, Y. A. & Kumar, R. Management of stored grain pest with special reference to Callosobruchus maculatus, a major pest of cowpea: a review. Heliyon. 8, e08703 (2022).Article 
PubMed 

Google Scholar 
de Groot, Pocock, M., Bonte, M. J. O. & Fernandez-Conradi, J. Valdés-Correcher, E. Citizen science and monitoring forest pests: a beneficial alliance? Curr. For. Rep. 9, 15–32 (2023).Article 
PubMed 

Google Scholar 
Cossich, V. R. A., Carlgren, D., Holash, R. J. & Katz, L. Technological breakthroughs in sport: current practice and future potential of artificial intelligence, virtual reality, augmented reality, and modern data visualization in performance analysis. Appl. Sci. 13, 12965 (2023).Article 
CAS 

Google Scholar 
Yassue, R. M., Galli, G., Fritsche-Neto, R. & Morota, G. Classification of plant growth-promoting bacteria inoculation status and prediction of growth-related traits in tropical maize using hyperspectral image and genomic data. Crop Sci. 63, 88–100 (2023).Article 
CAS 

Google Scholar 
Wei, D. P., Chen, J. Q., Luo, T., Long, T. & Wang, H. B. Classification of crop pests based on multi-scale feature fusion. Comput. Electron. Agric. 194, 106736 (2022).Article 

Google Scholar 
Bjekic, M. et al. Wall segmentation in 2D images using convolutional neural networks. PeerJ Comput. Sci. 9, 1–18 (2023).Article 

Google Scholar 
Aljohani, M. et al. An automated metaheuristic-optimized approach for diagnosing and classifying brain tumors based on a convolutional neural network. Results Eng. 23, 102459 (2024).Article 
CAS 

Google Scholar 
Apacionado, B. V. & Ahamed, T. Sooty mold detection on citrus tree canopy using deep learning algorithms. Sensors. (Basel Switzerland). 23, 8519 (2023).Article 
ADS 
PubMed 

Google Scholar 
Bischoff, V., Farias, K., Menzen, J. P. & Pessin, G. Technological support for detection and prediction of plant diseases: a systematic mapping study. Comput. Electron. Agric. 181, 105922 (2021).Article 

Google Scholar 
Chakrabarti, P., Sarkar, S. & Basu, P. Pesticide induced visual abnormalities in Asian honey bees (Apis cerana L.) in intensive agricultural landscapes. Chemosphere. 230, 51–58 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Zou, B. et al. Comparison of direct and indirect determinations of dynamic ventilation rate in a modern dairy free stall barn. Int. J. Agric. Biol. Eng. 13, 41–46 (2020).
Google Scholar 
Zhao, S., Sun, X. & Gai, L. Data enhancement and multi-feature learning model for pest classification. J. Intell. Fuzzy Syst. 45, 5409–5421 (2023).Article 

Google Scholar 
Taji, K. et al. An ensemble hybrid framework: a comparative analysis of metaheuristic algorithms for ensemble hybrid CNN features for plants disease classification. IEEE Access. 12, 61886–61906 (2024).Article 

Google Scholar 
Nagoor, S. & Jinny, S. V. A dual fuzzy with hybrid deep learning architecture based on CNN with hybrid metaheuristic algorithm for effective segmentation and classification. Int. J. Inf. Technol. 15, 531–543 (2023).
Google Scholar 
Shafik, W., Tufail, A., Liyanage, C. D. S. & Apong, R. A. A. H. M. Using a novel convolutional neural network for plant pests detection and disease classification. J. Sci. Food. Agric. 103, 5849–5861 (2023).Article 
CAS 
PubMed 

Google Scholar 
Arrechea-Castillo, D. A., Solano-Correa, Y. T., Muñoz-Ordóñez, J. F., Pencue-Fierro, E. L. & Figueroa-Casas, A. Multiclass land use and land cover classification of Andean sub-basins in Colombia with Sentinel-2 and deep learning. Remote Sens. 15, 2521 (2023).Article 
ADS 

Google Scholar 
Rastogi, S., Kumari, V., Sharma, V. & Ahmad, F. J. Colorimetric detection of oxytocin in bottle gourd using cysteamine functionalized gold nanoparticle (Cys-AuNPs). Food. Anal. Methods. 15, 2972–2983 (2022).Article 

Google Scholar 
Sulistyo, S. B., Wu, D., Woo, W. L., Dlay, S. S. & Gao, B. Computational deep intelligence vision sensing for nutrient content estimation in agricultural automation. IEEE Trans. Autom. Sci. Eng. 15, 1243–1257 (2018).Article 

Google Scholar 
Elshazly, E. H. et al. Identifying the anti-MERS-CoV and anti-HcoV-229E potential drugs from the Ginkgo biloba leaves extract and its eco-friendly synthesis of silver nanoparticles. Molecules. 28, 1375 (2023).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Napolitano, C. et al. Synthesis and insecticidal activity of N-(5-phenylpyrazin-2-yl)-benzamide derivatives: elucidation of mode of action on chitin biosynthesis through symptomology and genetic studies. Pestic. Biochem. Physiol. 199, 105771 (2024).Article 
CAS 
PubMed 

Google Scholar 
Saeed, F. et al. A robust approach for industrial small-object detection using an improved faster regional convolutional neural network. Sci. Rep. 11, 23390 (2021).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Bukumira, M. et al. Carrot grading system using computer vision feature parameters and a cascaded graph convolutional neural network. J. Electron. Imaging. 31, 061815 (2022).Article 
ADS 

Google Scholar 
Ni, L. L. et al. Monthly precipitation prediction at regional scale using deep convolutional neural networks. Hydrol. Process. 37, e14954 (2023).Article 

Google Scholar 
Prasath, B. & Akila, M. IoT-based pest detection and classification using deep features with enhanced deep learning strategies. Eng. Appl. Artif. Intell. 121, 105985 (2023).Article 

Google Scholar 
Cai, J. Z., Wu, J., Guo, C. L., Cai, S. H. & Cai, C. B. Ultrafast multi-slice chemical exchange saturation transfer imaging scheme based on segmented spatiotemporal encoding. Magn. Reson. Imaging. 60, 122–129 (2019).Article 
CAS 
PubMed 

Google Scholar 
Qiao, Y., Jiao, L. & Hou, B. High-quality depth up-sampling based on multi-scale SLIC. Electron. Lett. 54, 494–496 (2018).Article 
ADS 

Google Scholar 
Liu, W. P., Wang, J. F. & Chen, G. N. Research on image segmentation of multiphoton microscopic cell image based on SLIC super-pixels method. Basic. Clin. Pharmacol. Toxicol. 125, 28 (2019).
Google Scholar 
Bommisetty, R. M., Prakash, O. & Khare, A. Video superpixels generation through integration of curvelet transform and simple linear iterative clustering. Multimed. Tools Appl. 78, 25185–25219 (2019).Article 

Google Scholar 
Liu, Y. Y. et al. Identification and diagnosis of mammographic malignant architectural distortion using a deep learning based mask regional convolutional neural network. Front. Oncol. 13, 1119743 (2023).Article 
PubMed 
PubMed Central 

Google Scholar 
Mei, Y., Dai, Y. T. & Lei, Y. The influence of hierarchical masks on masked repetition priming: evidence from event-related potential investigation. Front. Hum. Neurosci. 13, 70 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Wang, B. Q. & Yang, F. L. Lightweight and privacy-preserving hierarchical federated learning mechanism for artificial intelligence-generated image content. J. Real-Time Image Process. 21, 149 (2024).Article 

Google Scholar 
Habiyaremye, A. & Korina, L. Indigenous knowledge systems in ecological pest control and post-harvest rice conservation techniques: sustainability lessons from Baduy communities. Sustain. 13, 9148 (2021).Article 

Google Scholar 
Zhang, Z. Y., Zhao, P., Jiang, Y. & Zhou, Z. H. Learning from incomplete and inaccurate supervision. IEEE Trans. Knowl. Data Eng. 34, 5854–5868 (2022).Article 

Google Scholar 
Ahadullah, M., Sapar, S. H., Al-Saidi, N. M. G. & Said, M. R. M. Competitive improvement of the time complexity to encode fractal image: by applying symmetric central pixel of the block. IEEE Access. 9, 5028–5045 (2021).Article 

Google Scholar 
Bakkouri, S. & Elyousfi, A. An adaptive CU size decision algorithm based on gradient boosting machines for 3D-HEVC inter-coding. Multimed. Tools Appl. 82, 32539–32557 (2023).Article 

Google Scholar 
Bhujade, V. G., Sambhe, V. & Banerjee, B. Digital image noise removal towards soybean and cotton plant disease using image processing filters. Expert Syst. Appl. 246, 123031 (2024).Article 

Google Scholar 
Elumalai, G. & Ganesan, M. Deep learning based hand wrist segmentation using Mask R-CNN. Int. Arab. J. Inform. Technol. 19, 785–792 (2022).
Google Scholar 
GitHub. hlydecker/hierarchical-rcnn (Public). https://github.com/hlydecker/hierarchical-rcnnNakach, F. Z., Zerouaoui, H. & Idri, A. Binary classification of multi-magnification histopathological breast cancer images using late fusion and transfer learning. Data Technol. Appl. 57, 668–695 (2023).
Google Scholar 
Song, X. F. et al. A clinical decision model based on machine learning for ptosis. BMC Ophthalmol. 21, 169 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Karanikola, A., Liapis, C. M. & Kotsiantis, S. Investigating cluster validation metrics for optimal number of clusters determination. Intell. Decis. Technol. 15, 809–824 (2021).
Google Scholar 
Saleem, M. H., Potgieter, J. & Arif, K. M. Automation in Agriculture by Machine and Deep Learning techniques: a review of recent developments. Precis. Agric. 22, 2053–2091 (2021).Article 

Google Scholar 
Mukhopadhyay, A. K., Majumder, S. & Chakrabarti, I. Systematic realization of a fully connected deep and convolutional neural network architecture on a field programmable gate array. Comput. Electr. Eng. 97, 107628 (2022).Article 

Google Scholar 
Kuo, J. K., Wu, J. J., Huang, P. H. & Cheng, C. Y. Inspection of sandblasting defect in investment castings by deep convolutional neural network. Int. J. Adv. Manuf. Technol. 120, 2457–2468 (2022).Article 

Google Scholar 
Maeda-Gutiérrez, V. et al. Comparison of convolutional neural network architectures for classification of tomatoplant diseases. Appl. Sci. 10, 1245 (2020).Article 

Google Scholar