MetaCOVID: A Siamese neural network framework with contrastive loss for n-shot diagnosis of COVID-19 patients

Deep Residual Learning for Image Recognition

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Very Deep Convolutional Networks for Large-Scale Image Recognition

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Going deeper with convolutions

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Xception: Deep Learning with Depthwise Separable Convolutions

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UNet++: A Nested U-Net Architecture for Medical Image Segmentation

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Dimensionality Reduction by Learning an Invariant Mapping

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Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

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COVID-19 infection: Emergence, transmission, and characteristics of human coronaviruses

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COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images

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A Convolutional-Transformer Model for FFR and iFR Assessment From Coronary Angiography

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Self-paced contrastive learning for knowledge tracing

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Pneumothorax Recognition Neural Network Based on Feature Fusion of Frontal and Lateral Chest X-Ray Images

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McS-Net: Multi-class Siamese network for severity of COVID-19 infection classification from lung CT scan slices

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Ensembling shallow siamese architectures to assess functional asymmetry in Alzheimer’s disease progression

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Age-based disease prediction and health monitoring: integrating explainable AI and deep learning techniques

Sushmitha, G., & Utukuru, S. (2025) · Iran Journal of Computer Science · doi:10.1007/s42044-024-00223-7 · Cited by 11

A transfer learning-based deep learning approach for automated COVID-19 diagnosis with audio data

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One-Shot Retail Product Identification Based on Improved Siamese Neural Networks

Wang, C., Huang, C., Zhu, X., & Zhao, L. (2022) · Circuits Systems and Signal Processing · doi:10.1007/s00034-022-02062-y · Cited by 12

A narrative review of medical image processing by deep learning models: origin to COVID-19

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Noninvasive COVID-19 Screening Using Deep-Learning-Based Multilevel Fusion Model With an Attention Mechanism

Hossain, M. S., & Shorfuzzaman, M. (2023) · IEEE Open Journal of Instrumentation and Measurement · doi:10.1109/ojim.2023.3303944 · Cited by 12

Detecting COVID-19 Pneumonia over Fuzzy Image Enhancement on Computed Tomography Images

Alzahrani, A., Bhuiyan, M. A.-A., & Akhter, F. (2022) · Computational and Mathematical Methods in Medicine · doi:10.1155/2022/1043299 · Cited by 11

Intelligent diagnosis of coronavirus with computed tomography images using a deep learning model

Šarac, M., Mravik, M., Jovanovic, D., Strumberger, I., Zivkovic, M. Z., & Bačanin, N. (2022) · Journal of Electronic Imaging · doi:10.1117/1.jei.32.2.021406 · Cited by 11

Swin MoCo: Improving parotid gland MRI segmentation using contrastive learning

Xu, Z., Dai, Y., Liu, F., Wu, B., Chen, W., & Shi, L. (2024) · Medical Physics · doi:10.1002/mp.17128 · Cited by 10

The Application of Deep Learning in Enhancing the Effectiveness of Islamic Religious Education Curriculum in Madrasahs

Idham, I., Rokimin, R., Akhirudin, M. T., Zh, M. H. R., & Thaariq, Z. Z. A. (2026) · Management of Education Jurnal Manajemen Pendidikan Islam · doi:10.18592/moe.v12i1.20058 · Cited by 10

One Shot Learning with class partitioning and cross validation voting (CP-CVV)

Domingo, J. D., Medina, R., & Rodrigo, L. M. G. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.109797 · Cited by 10

A high-accuracy lightweight network model for X-ray image diagnosis: A case study of COVID detection

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Deep-Learning-Assisted Digital Fluorescence Immunoassay on Magnetic Beads for Ultrasensitive Determination of Protein Biomarkers

Zhang, J., Zhou, W., Qi, H., & He, X. (2025) · Analytical Chemistry · doi:10.1021/acs.analchem.4c05877 · Cited by 9

UMLF-COVID: an unsupervised meta-learning model specifically designed to identify X-ray images of COVID-19 patients

Miao, R., Dong, X. L., Xie, S., Liang, Y., & Lo, S. (2021) · BMC Medical Imaging · doi:10.1186/s12880-021-00704-2 · Cited by 9

COVID-19 contact tracking by group activity trajectory recovery over camera networks

Wang, C., Wang, X., Wang, Z., Zhu, W., & Hu, R. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108908 · Cited by 9

Improving Siamese Neural Networks with Border Extraction Sampling for the use in Real-Time Network Intrusion Detection

Pawlicki, M., Kozik, R., & Choraś, M. (2023) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191496 · Cited by 9

A few-shot approach for COVID-19 screening in standard and portable chest X-ray images

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GLMR-Net: Global-to-local mutually reinforcing network for pneumonia segmentation and classification

Dong, A., Liu, J., Lv, G., & Cheng, J. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.111371 · Cited by 8

Prediction of Sperm Retrieval Outcomes Based on Testicular Ultrasound Images and Dense Convolutional Sparse Coding

Qi, H.-X., Yang, S., Miao, Y., Cui, L.-G., Xue, H., Hua, J., Hong, K., & Fang, Y.-Y. (2026) · IEEE Sensors Journal · doi:10.1109/jsen.2026.3653513 · Cited by 8

Hybrid deep learning metaheuristic ensemble framework for enhanced COVID-19 classification using ResNet and particle swarm optimization

Abdollahi, J., Nouri-Moghaddam, B., Mirzaei, A., Derakhshanfard, N., & ebrahimi, T. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-00922-z · Cited by 8

Multi-contrast learning-guided lightweight few-shot learning scheme for predicting breast cancer molecular subtypes

Pan, X., Wang, P., Jia, S., Wang, Y., Liu, Y., Zhang, Y., & Jiang, C. (2024) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-024-03031-0 · Cited by 8

Post-COVID highlights: Challenges and solutions of artificial intelligence techniques for swift identification of COVID-19

Fang, Y., Xing, X., Wang, S., Walsh, S. L. F., & Yang, G. (2024) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2024.102778 · Cited by 8

DeepHealth: A Secure Framework to Manage Health Certificates Through Medical IoT, Blockchain and Deep Learning

Rakib, G. A., Islam, M. S., Rahman, M. A., Syed, A. M., Hossain, M. S., Alrajeh, N. A., & Saddik, A. E. (2021) · IEEE International Symposium on Medical Measurements and Applications (MeMeA) · doi:10.1109/memea52024.2021.9478691 · Cited by 8

AI based Algorithms of Path Planning, Navigation and Control for Mobile Ground Robots and UAVsPreprint

Zhang, J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.00910 · Cited by 9

Hybrid unsupervised representation learning and pseudo-label supervised self-distillation for rare disease imaging phenotype classification with dispersion-aware imbalance correction

Sun, J., Wei, D., Wang, L., & Zheng, Y. (2024) · Medical Image Analysis · doi:10.1016/j.media.2024.103102 · Cited by 6

A Siamese Convolutional Neural Network for Identifying Mild Traumatic Brain Injury and Predicting Recovery

Koochaki, F., & Najafizadeh, L. (2024) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2024.3391067 · Cited by 6

Similar Face Detection for Indian Faces using Siamese Neural Networks

Devi, P. R., Rachamallu, Y., Gogineni, N., & Ruchitha, M. (2021) · International Conference for Emerging Technology (INCET) · doi:10.1109/incet51464.2021.9456199 · Cited by 6

Advanced 3D Deep Non-Local Embedded System for Self-Augmented X-Ray-based COVID-19 Assessment

Rundo, F., Genovese, A., Leotta, R., Scotti, F., Piuri, V., & Battiato, S. (2021) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw54120.2021.00051 · Cited by 6

Thick Data Analytics for Small Training Samples Using Siamese Neural Network and Image Augmentation

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Supervised Anomaly Detection in Univariate Time-Series Using 1D Convolutional Siamese Networks

Chatterjee, A., Thambawita, V. L., Riegler, M. A., & Halvorsen, P. (2025) · IEEE Access · doi:10.1109/access.2025.3561375 · Cited by 5

A study on fast recognition of multi-class bridge damage based on improved Siamese ResNet50 with limited samples

Chen, L., Yao, H., Gan, K., Ye, Y., Ng, C., & Fu, J. (2025) · Engineering Structures · doi:10.1016/j.engstruct.2025.121781 · Cited by 5

A Comparative Evaluation of Meta-Learning Models for Few-Shot Chest X-Ray Disease Classification

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A Self-attentive Meta-learning Approach for Image-Based Few-Shot Disease Detection

Ouahab, A., Ahmed, O. B., & Fernández-Maloigne, C. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16876-5_12 · Cited by 5

Machine-Learning-Based COVID-19 Detection with Enhanced cGAN Technique Using X-ray Images

Hamdi, M., Ksibi, A., Ayadi, M. F., Elmannai, H., & Alzahrani, A. I. A. (2022) · Electronics · doi:10.3390/electronics11233880 · Cited by 5

An enhanced ant colony optimizer with Cauchy-Gaussian fusion and novel movement strategy for multi-threshold COVID-19 X-ray image segmentation

Zhao, X., Liu, L., Heidari, A. A., Chen, Y., Ma, B. J., Chen, H., & Quan, S. (2023) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2023.1126783 · Cited by 5

A Survey on Deep Learning Advances and Emerging Issues in Pneumonia and COVID19 Prediction

Makhanov, N., Tu, N. A., & Wong, K. (2022) · IEEE International Conference on Big Data and Smart Computing (BigComp) · doi:10.1109/bigcomp54360.2022.00029 · Cited by 5

COVID-19 Detection from X-Ray Images using Convoluted Neural Networks: A Literature Review

Alrusaini, O. A. (2022) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2022.0130313 · Cited by 5

Automated segmentation of child-clinician speech in naturalistic clinical contexts

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Classification of Heart (Cardiovascular) Disease using the SVM Method

Abidin, M., Munzir, M. M., Imantoyo, A., Grendis, N. W. B., San, A. S. H., Mostfa, A. A., Furizal, F., & Sharkawy, A. (2025) · Indonesian Journal of Modern Science and Technology · doi:10.64021/ijmst.1.1.9-15.2025 · Cited by 4

Meta-Learning Frameworks in Lung Disease Detection: A survey

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Novel semi-supervised learning approach for descriptor generation using artificial neural networks

Alwindawi, A. F., Osman Nuri, U. C. A. N., İbrahim, A. A., & Yusuf, A. (2022) · Soft Computing · doi:10.1007/s00500-022-06742-4 · Cited by 4

Self-Supervised Contrastive Learning for Covid-19 Classification from Computed Tomography Images

Mohit, K., Gupta, R. K., & Kumar, B. (2022) · IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) · doi:10.1109/upcon56432.2022.9986406 · Cited by 4

Data Science in Healthcare Monitoring Under Covid-19 Detection by Extended Hybrid Leader-Based Compressed Neural Network

Thandu, A. L., Thommandru, V. S., & Pradeepini, G. (2023) · New Generation Computing · doi:10.1007/s00354-023-00225-2 · Cited by 4

Driver behaviour prediction and enhanced ad hoc on‐demand distance vector routing protocol in VANET

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CovSeg-Unet: End-to-End Method-based Computer-Aided Decision Support System in Lung COVID-19 Detection on CT Images

Biach, F. Z. E., Iala, I., Laanaya, H., & Minaoui, K. (2022) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2022.0130162 · Cited by 4

Combined model-driven and dual-cycle interactive strategy few-shot learning scheme for predicting breast cancer molecular subtypes based on DCE-MRI

Hong, X., Zhang, L., Ding, L., Li, L., Li, L., Liu, J., Zhang, Y., & Pan, X. (2025) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2025.108923 · Cited by 3

PFSNet: A prototypical federated siamese network for few-shot cervical cancer detection

Sahoo, P., Gala, J. P., Saha, S., Chowdhury, S., & Mondal, S. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.109265 · Cited by 3

Adaptation: Blessing or Curse for Higher Way Meta-Learning

Aimen, A., Sidheekh, S., Ladrecha, B., Ahuja, H., & Krishnan, N. C. (2023) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2023.3301826 · Cited by 3

Siamese neural network-enhanced electrocardiography can re-identify anonymized healthcare data

Macierzanka, K., Sau, A., Patlatzoglou, K., Pastika, L., Sieliwończyk, E., Gurnani, M., Peters, N. S., Waks, J. W., Kramer, D. B., & Ng, F. S. (2025) · European Heart Journal - Digital Health · doi:10.1093/ehjdh/ztaf011 · Cited by 3

RAFFCDNet: A diagnostic network based on adaptive feature fusion and class-distance-based loss function for occupational pneumoconiosis

Zhao, Q., Guo, Y., & Gong, D. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.107957 · Cited by 3

NetraNet: A similarity learning method for diabetic retinopathy classification and clinical diagnosis

Kapoor, P., & Arora, S. (2025) · International Journal of Diabetes in Developing Countries · doi:10.1007/s13410-025-01577-9 · Cited by 3

Siamese Networks for Speaker Identification on Resource-Constrained Platforms

Jie, L. J., Zabidi, M. M. A., Sadiah, S., & Rahman, A. A.-H. A. (2023) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2622/1/012014 · Cited by 3

Review of Deep Learning: Architectures, Applications and Challenges

Sirmorya, A., Chaudhari, M., & Balasinor, S. (2022) · International Journal of Computer Applications · doi:10.5120/ijca2022922164 · Cited by 3

Automatic diagnosis of COVID-19 from chest X-ray images using transfer learning-based deep features and machine learning models

Kumar, P. V., Gupta, A. K., Hazarika, B. B., & Gupta, D. (2025) · China Communications · doi:10.23919/jcc.ja.2022-0273 · Cited by 3

Deep metric learning for few-shot X-ray image classificationPreprint

Prokop, J., Montalt‐Tordera, J., Jaworek-Korjakowska, J., & Mohammadi, S. (2023) · medRxiv · doi:10.1101/2023.08.27.23294690 · Cited by 3

Optimization of matching networks with transfer learning in few-shot pneumonia detection

Doreen, A., Mwangi, W. R., & Muriithi, P. (2025) · Discover Applied Sciences · doi:10.1007/s42452-025-07376-5 · Cited by 2

Federated learning-based virtual dual-energy CT generation from single-energy CT for gout detection

Dong, Y., Liu, M., Feng, J., Yang, Y., Dai, Y., & Jin, Z. (2025) · Digital Health · doi:10.1177/20552076251375570 · Cited by 2

Few-shot pneumonia detection using Siamese networks and transfer learning on chest X-ray images

Doreen, A., Mwangi, W. R., & Muriithi, P. (2025) · Discover Artificial Intelligence · doi:10.1007/s44163-025-00468-6 · Cited by 2

An enhanced privacy-preserving federated few-shot learning framework for respiratory disease diagnosis

Wang, M., Duan, Z., Xue, D., Liu, F., & Zhang, Z. (2026) · Applied Soft Computing · doi:10.1016/j.asoc.2026.114586 · Cited by 2

A low-resolution real-time face recognition using extreme learning machine and its variants

Rajpal, A., Sehra, K., Mishra, A., & Chetty, G. (2023) · The Imaging Science Journal · doi:10.1080/13682199.2023.2183544 · Cited by 2

Contrastive Learning Embedded Siamese Neural Network for the Assessment of Fatty Liver

Mohit, K., Shukla, A., Gupta, R. K., Singh, P. K., Agarwal, K., & Kumar, B. (2023) · IEEE Region 10 Conference (TENCON) · doi:10.1109/tencon58879.2023.10322413 · Cited by 2

Improving deep learning based bluespotted ribbontail ray (Taeniura Lymma) recognition

Levy, A., Barash, A., Zaguri, C., Hadad, A., & Polsky, P. (2024) · Ecological Informatics · doi:10.1016/j.ecoinf.2024.102737 · Cited by 2

Optimizing Pneumonia Classification on Pediatric Chest X-Ray Images Using ConvNeXt Network

Prasetyo, S. Y., Prabowo, A. S., Santy, S., & Pepita, P. (2024) · International Conference on Information Management and Technology (ICIMTech) · doi:10.1109/icimtech63123.2024.10780843 · Cited by 2

CD Loss: A Class-Center Based Distribution Loss for Discriminative Feature Learning in Medical Image Classification

Zhou, Y., Du, J., Liu, Y., Qiu, Y., & Wang, T. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87358-5_51 · Cited by 2

On Deep Learning for Dorsal Hand Vein Recognition

Bagchi, S., Chanda, G., Agarwal, A., & Ratha, N. (2022) · IEEE Western New York Image and Signal Processing Workshop (WNYISPW) · doi:10.1109/wnyispw57858.2022.9982726 · Cited by 2

Time Series Analysis with Systematic Survey on Covid-19 Based Predictive Studies During Pandemic Period using Enhanced Machine Learning Techniques

Rajeswari, K., Vispute, S. R., Maitre, A., Kharat, R. S., Aher, A., Vivekanandan, N., Kachhoria, R., & Jaiswal, S. (2023) · International Journal of Online and Biomedical Engineering (iJOE) · doi:10.3991/ijoe.v19i07.39089 · Cited by 2

Identifying radiogenomic associations of breast cancer based on DCE‐MRI by using Siamese Neural Network with manufacturer bias normalization

Chen, J., Zeng, H., Cheng, Y., & Yang, B. (2024) · Medical Physics · doi:10.1002/mp.17266 · Cited by 2

Enhancing the Generalization Performance of Few-Shot Image Classification with Self-Knowledge Distillation

Liang, L. I., Jin, W., HUANG, Y., & Junxiao, R. E. N. (2022) · Studies in Informatics and Control · doi:10.24846/v31i2y202207 · Cited by 2

Recent Advances and Challenges of Edge AI and IoT Assisted Covid-19 Alike Detection Systems

Kamruzzaman, M. M., Hossin, M. A., & Alrashdi, I. (2022) · IEEE Globecom Workshops (GC Wkshps) · doi:10.1109/gcwkshps56602.2022.10008591 · Cited by 2

Few-Shot Image Classification for Automatic COVID-19 Diagnosis

Cores, D., Vila-Blanco, N., Mucientes, M., & Carreira, M. J. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-36616-1_43 · Cited by 2

Unlocking Comparative Plant Scoring with Siamese Neural Networks and Pairwise Pseudo Labelling

Hartley, Z. K. J., Lind, R. J., Smith, N., Collison, B., & French, A. P. (2023) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw60793.2023.00075 · Cited by 2

Heuristic Once Learning for Image & Text Duality Information Processing

Weigang, L., Martins, L., Ferreira, N. B. F., Miranda, C., Althoff, L. D. S., Pessoa, W., Farias, M. C. Q., Jacobi, R. P., & Ayala-Rincón, M. (2022) · IEEE Smart World Congress (SWC) · doi:10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00195 · Cited by 1

Deep Learning Applied to COVID-19 Detection in X-Ray Images

Arteaga-Arteaga, H. B., delaPava, M., Mora-Rubio, A., Bravo-Ortíz, M. A., Alzate-Grisales, J. A., Arias-Garzón, D., López-Murillo, L. H., Buitrago-Carmona, F., Villa-Pulgarín, J. P., Mercado-Ruiz, E., et al. (2022) · Advances in medical diagnosis, treatment, and care (AMDTC) book series · doi:10.4018/978-1-6684-2304-2.ch007 · Cited by 2

FLPanGuard a Conceptual FL-Based Framework to Detect and Fight New Pandemics

Chouja, I., Saoud, S., Sadik, M., & Sbaï, A. (2024) · International Journal of Online and Biomedical Engineering (iJOE) · doi:10.3991/ijoe.v20i16.51895 · Cited by 1

Towards Objective Assessment of Cleft Surgical Outcomes: A GAN-Inpainting Based Approach

Atputharuban, D. A., Theopold, C., & Lawlor, A. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-06007-5_10 · Cited by 1

DALGACIK EVRİŞİMSEL SİNİR AĞI YÖNTEMİ İLE KORONAVİRÜS HASTALIĞININ TESPİTİ

Çalışkan, A. (2023) · Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi · doi:10.17780/ksujes.1208283 · Cited by 1

A turning point few-shot learning for COVID-19 diagnosis

Qain, L., Bouteraa, Y., Vaiyapuri, T., & Haung, Y. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.108337 · Cited by 1

Siamese Networks and Adversarial Attacks: An Overview

Shaw, L., Hebli, P., & Ekin, T. (2024) · IEEE Conference on Prognostics and Health Management · doi:10.1109/icphm61352.2024.10626656 · Cited by 1

A Siamese neural network-based diagnosis of COVID-19 using chest X-rays

Taş, E., & Atli, A. H. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-10326-8 · Cited by 1

An Optimized Machine Learning Algorithms for COVID-19 Disease

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TDA-SSNN: Efficient Hybrid Top-Down Attention Siamese Sparrow Neural Network for Automatic Drone Navigation

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