Transfer learning for versatile plant disease recognition with limited data
Xu, Mingle; Yoon, Sook; Jeong, Yongchae; Park, Dong Sun
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2022.1010981
30 Referensi untuk Research Gap & Novelty
Domain-Generalized Self-Supervised Vision Transformer Using Masked Autoencoder for Fig Leaf Health Classification
30 artikel jurnal · 23 Q1 dan 7 Q2 · tahun terbit 2021–2026.
Kuartil adalah SCImago SJR edisi 2024 pada kategori yang dicantumkan; bukan CiteScore, bukan otomatis kuartil tahun publikasi, dan bukan jaminan kualitas setiap artikel. Sebagian bukti profil diperoleh dari ekstrak terindeks karena akses langsung SCImago terhalang Cloudflare.
PDF penerbit berlisensi CC BY 4.0 dan tidak diubah. Penulis, sumber asli, DOI serta lisensi tersedia untuk atribusi. Ini paket 30 artikel dari 10 jurnal, bukan 30 jurnal berbeda.
Pemetaan gap bersifat awal: artikel kelompok A/C ditelaah pada bagian terpilih; kelompok B baru diverifikasi metadata, PDF dan copyright. Novelty belum dinyatakan terbukti dan belum ada hasil eksperimen penelitian daun tin yang dibuat-buat.
Menampilkan 30 dari 30 artikel
Plant disease classification in the wild using vision transformers and mixture of experts
Salman, Zafar; Muhammad, Abdullah; Han, Dongil
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2025.1522985
FOTCA: hybrid transformer-CNN architecture using AFNO for accurate plant leaf disease image recognition
Hu, Bo; Jiang, Wenqian; Zeng, Juan; Cheng, Chen; He, Laichang
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2023.1231903
PMVT: a lightweight vision transformer for plant disease identification on mobile devices
Li, Guoqiang; Wang, Yuchao; Zhao, Qing; Yuan, Peiyan; Chang, Baofang
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2023.1256773
TrIncNet: a lightweight vision transformer network for identification of plant diseases
Gole, Pushkar; Bedi, Punam; Marwaha, Sudeep; Haque, Md. Ashraful; Deb, Chandan Kumar
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2023.1221557
Automatic classification of ligneous leaf diseases via hierarchical vision transformer and transfer learning
Han, Dianyuan; Guo, Chunhua
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2023.1328952
Zero-exemplar deep continual learning for crop disease recognition: a study of total variation attention regularization in vision transformers
Wang, Boyuan
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2023.1283055
Classification of Plant Leaf Disease Recognition Based on Self-Supervised Learning
Yuzhi Wang; Yunzhen Yin; Yaoyu Li; Tengteng Qu; Zhaodong Guo; Mingkang Peng; Shujie Jia; Qiang Wang; Wuping Zhang; Fuzhong Li
Agronomy · SJR Q1 (2024, Agronomy and Crop Science)
DOI: 10.3390/agronomy14030500
A Unified Self-Supervised Framework for Plant Disease Detection on Laboratory and In-Field Images
Xiaoli Huan; Bernard Chen; Hong Zhou
Electronics · SJR Q2 (2024, Computer Networks and Communications)
DOI: 10.3390/electronics14173410
Instance-Aware Plant Disease Detection by Utilizing Saliency Map and Self-Supervised Pre-Training
Taejoo Kim; Hyeongjun Kim; Kyeonghoon Baik; Yukyung Choi
Agriculture · SJR Q1 (2024, Agronomy and Crop Science)
DOI: 10.3390/agriculture12081084
A deep learning based approach for automated plant disease classification using vision transformer
Borhani, Yasamin; Khoramdel, Javad; Najafi, Esmaeil
Scientific Reports · SJR Q1 (2024, Multidisciplinary)
DOI: 10.1038/s41598-022-15163-0
A multi-source domain feature adaptation network for potato disease recognition in field environment
Gao, Xueze; Feng, Quan; Wang, Shuzhi; Zhang, Jianhua; Yang, Sen
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2024.1471085
From laboratory to field: cross-domain few-shot learning for crop disease identification in the field
Yang, Sen; Feng, Quan; Zhang, Jianhua; Yang, Wanxia; Zhou, Wenwei; Yan, Wenbo
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2024.1434222
Embracing limited and imperfect training datasets: opportunities and challenges in plant disease recognition using deep learning
Xu, Mingle; Kim, Hyongsuk; Yang, Jucheng; Fuentes, Alvaro; Meng, Yao; Yoon, Sook; Kim, Taehyun; Park, Dong Sun
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2023.1225409
Plant disease recognition datasets in the age of deep learning: challenges and opportunities
Xu, Mingle; Park, Ji-Eun; Lee, Jaehwan; Yang, Jucheng; Yoon, Sook
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2024.1452551
Open Set Self and Across Domain Adaptation for Tomato Disease Recognition With Deep Learning Techniques
Fuentes, Alvaro; Yoon, Sook; Kim, Taehyun; Park, Dong Sun
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2021.758027
A New Deep Learning-based Dynamic Paradigm Towards Open-World Plant Disease Detection
Dong, Jiuqing; Fuentes, Alvaro; Yoon, Sook; Kim, Hyongsuk; Jeong, Yongchae; Park, Dong Sun
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2023.1243822
Revolutionizing agriculture with artificial intelligence: plant disease detection methods, applications, and their limitations
Jafar, Abbas; Bibi, Nabila; Naqvi, Rizwan Ali; Sadeghi-Niaraki, Abolghasem; Jeong, Daesik
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2024.1356260
Analysis of Few-Shot Techniques for Fungal Plant Disease Classification and Evaluation of Clustering Capabilities Over Real Datasets
Egusquiza, Itziar; Picon, Artzai; Irusta, Unai; Bereciartua-Perez, Arantza; Eggers, Till; Klukas, Christian; Aramendi, Elisabete; Navarra-Mestre, Ramon
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2022.813237
Few-shot learning approach with multi-scale feature fusion and attention for plant disease recognition
Lin, Hong; Tse, Rita; Tang, Su-Kit; Qiang, Zhen-ping; Pau, Giovanni
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2022.907916
Cross-scale detection and cross-crop generalization verification of tomato diseases in complex agricultural environments
Hu, Jinghuan; Li, Jinying; Wang, Heyang
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2025.1644271
Quantifying the reliability gap in cross-domain plant disease classification: benchmarking the limited efficacy of standard mitigation techniques under controlled-to-field shift
Xiang, Kun; Shi, Danxi; Zhu, Xiangbo
Frontiers in Plant Science · SJR Q1 (2024, Plant Science)
DOI: 10.3389/fpls.2026.1826962
Domain Generalization Through Data Augmentation: A Survey of Methods, Applications, and Challenges
Junjie Mai; Chongzhi Gao; Jun Bao
Mathematics · SJR Q2 (2024, Computer Science (miscellaneous))
DOI: 10.3390/math13050824
Implicit Sharpness-Aware Minimization for Domain Generalization
Mingrong Dong; Yixuan Yang; Kai Zeng; Qingwang Wang; Tao Shen
Remote Sensing · SJR Q1 (2024, Earth and Planetary Sciences (miscellaneous))
DOI: 10.3390/rs16162877
A Causality-Aware Perspective on Domain Generalization via Domain Intervention
Youjia Shao; Shaohui Wang; Wencang Zhao
Electronics · SJR Q2 (2024, Signal Processing)
DOI: 10.3390/electronics13101891
Survey on Self-Supervised Learning: Auxiliary Pretext Tasks and Contrastive Learning Methods in Imaging
Saleh Albelwi
Entropy · SJR Q2 (2024, Information Systems)
DOI: 10.3390/e24040551
To Compress or Not to Compress—Self-Supervised Learning and Information Theory: A Review
Ravid Shwartz Ziv; Yann LeCun
Entropy · SJR Q2 (2024, Information Systems)
DOI: 10.3390/e26030252
Multi-View Masked Autoencoder for General Image Representation
Seungbin Ji; Sangkwon Han; Jongtae Rhee
Applied Sciences · SJR Q2 (2024, Computer Science Applications)
DOI: 10.3390/app132212413
Masked Image Modeling: A Survey
Vlad Hondru; Florinel Alin Croitoru; Shervin Minaee; Radu Tudor Ionescu; Nicu Sebe
International Journal of Computer Vision · SJR Q1 (2024, Artificial Intelligence)
DOI: 10.1007/s11263-025-02524-1
Comparing Vision Transformers and Convolutional Neural Networks for Image Classification: A Literature Review
José Maurício; Inês Domingues; Jorge Bernardino
Applied Sciences · SJR Q2 (2024, Computer Science Applications)
DOI: 10.3390/app13095521