Cover Image

Leveraging deep learning for plant disease identification: a bibliometric analysis in SCOPUS from 2018 to 2024

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Albert, Enow Takang Achuo, Bille, Ngalle Hermine, Leonard, Ngonkeu Mangaptche Eddy
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Pupil referral units ( PRUs ) and alternative education provision; a think piece on making a case for parental choice for children with SEND
by: Linda O. Enow, et al.
Published: (2024)

Comparison of deep learning and conventional methods for disease onset prediction
by: John, Luis H., et al.
Published: (2024)

Physics-informed deep learning for infectious disease forecasting
by: Qian, Ying, et al.
Published: (2025)

Fairness-enhancing mixed effects deep learning improves fairness on in- and out-of-distribution clustered (non-iid) data
by: Nguyen, Son, et al.
Published: (2023)

Heart disease risk prediction using deep learning techniques with feature augmentation
by: García-Ordás, María Teresa, et al.
Published: (2024)

Feature engineering vs. deep learning for paper section identification: Toward applications in Chinese medical literature
by: Zhou, Sijia, et al.
Published: (2024)

Leaf diseases detection using deep learning methods
by: Fatimi, El Houcine El
Published: (2024)

A bibliometric analysis of the SCOPUS ‐indexed research on written peer feedback
by: Hooman Saeli, et al.
Published: (2025)

Generalization analysis with deep ReLU networks for metric and similarity learning
by: Zhou, Junyu, et al.
Published: (2024)

Hair and scalp disease detection using deep learning
by: Sultanpure, Kavita, et al.
Published: (2024)

Leveraging Axis-Aligned Subspaces for High-Dimensional Bayesian Optimization with Group Testing
by: Hellsten, Erik, et al.
Published: (2025)

Mathematical analysis of the gradients in deep learning
by: Dereich, Steffen, et al.
Published: (2025)

Adaptive parameters identification for nonlinear dynamics using deep permutation invariant networks
by: Elaarabi, Mouad, et al.
Published: (2025)

Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling
by: Galioto, Nicholas, et al.
Published: (2024)

DySurv: dynamic deep learning model for survival analysis with conditional variational inference
by: Mesinovic, Munib, et al.
Published: (2023)

Dragonfly: a modular deep reinforcement learning library
by: Viquerat, Jonathan, et al.
Published: (2025)

An overview of condensation phenomenon in deep learning
by: Xu, Zhi-Qin John, et al.
Published: (2025)

Towards efficient representation identification in supervised learning
by: Ahuja, Kartik, et al.
Published: (2022)

scMEDAL for the interpretable analysis of single-cell transcriptomics data with batch effect visualization using a deep mixed effects autoencoder
by: Andrade, Aixa X., et al.
Published: (2024)

Assessing wildfire susceptibility in Iran: Leveraging machine learning for geospatial analysis of climatic and anthropogenic factors
by: Masoudian, Ehsan, et al.
Published: (2025)

Domain-randomized deep learning for neuroimage analysis
by: Hoffmann, Malte
Published: (2025)

TransECG: Leveraging Transformers for Explainable ECG Re-identification Risk Analysis
by: Wang, Ziyu, et al.
Published: (2025)

LaCoGSEA: Unsupervised deep learning for pathway analysis via latent correlation
by: Zheng, Zhiwei, et al.
Published: (2026)

Automated identification of Ichneumonoidea wasps via YOLO-based deep learning: Integrating HiresCam for Explainable AI
by: Pinheiro, Joao Manoel Herrera, et al.
Published: (2026)

Statistically guided deep learning
by: Kohler, Michael, et al.
Published: (2025)

Mathematical theory of deep learning
by: Petersen, Philipp, et al.
Published: (2024)

Generalized Bayesian deep reinforcement learning
by: Roy, Shreya Sinha, et al.
Published: (2024)

Self-supervised contrastive learning performs non-linear system identification
by: Laiz, Rodrigo González, et al.
Published: (2024)

Deep learning-based fault identification in condition monitoring
by: Dhungana, Hariom, et al.
Published: (2024)

Machine-learning-based particle identification with missing data
by: Kasak, Miłosz, et al.
Published: (2023)

A 3D deep learning classifier and its explainability when assessing coronary artery disease
by: Cheung, Wing Keung, et al.
Published: (2023)

Empirical risk minimization algorithm for multiclass classification of S.D.E. paths
by: Denis, Christophe, et al.
Published: (2025)

Towards a theory of learning dynamics in deep state space models
by: Smékal, Jakub, et al.
Published: (2024)

Memorization in deep learning: A survey
by: Wei, Jiaheng, et al.
Published: (2024)

Nonparametric logistic regression with deep learning
by: Yara, Atsutomo, et al.
Published: (2024)

A general framework for deep learning
by: Kengne, William, et al.
Published: (2025)

Coalgebras for categorical deep learning: Representability and universal approximation
by: Mašulović, Dragan
Published: (2026)

An invariance constrained deep learning network for PDE discovery
by: Chen, Chao, et al.
Published: (2024)

Hadamard product in deep learning: Introduction, Advances and Challenges
by: Chrysos, Grigorios G, et al.
Published: (2025)

Overview frequency principle/spectral bias in deep learning
by: Xu, Zhi-Qin John, et al.
Published: (2022)