Imagen de Portada

Learning Under Extreme Data Scarcity: Subject-Level Evaluation of Lightweight CNNs for fMRI-Based Prodromal Parkinsons Detection

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Rahman, Naimur
Formato:	Preprint
Publicado:	2026
Materias:	Computer Vision and Pattern Recognition Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

MindFormer: Semantic Alignment of Multi-Subject fMRI for Brain Decoding
por: Han, Inhwa, et al.
Publicado: (2024)

Swin fMRI Transformer Predicts Early Neurodevelopmental Outcomes from Neonatal fMRI
por: Styll, Patrick, et al.
Publicado: (2024)

Multimodal Deep Learning for Dynamic and Static Neuroimaging: Integrating MRI and fMRI for Alzheimer Disease Analysis
por: Kujur, Anima, et al.
Publicado: (2026)

Lightweight CNNs for Embedded SAR Ship Target Detection and Classification
por: Kresse, Fabian, et al.
Publicado: (2025)

Efficient Multi Subject Visual Reconstruction from fMRI Using Aligned Representations
por: Zangos, Christos, et al.
Publicado: (2025)

SpaRG: Sparsely Reconstructed Graphs for Generalizable fMRI Analysis
por: González, Camila, et al.
Publicado: (2024)

Towards a general-purpose foundation model for fMRI analysis
por: Wang, Cheng, et al.
Publicado: (2025)

Duala: Dual-Level Alignment of Subjects and Stimuli for Cross-Subject fMRI Decoding
por: Li, Shumeng, et al.
Publicado: (2026)

Brain Tumor Detection in MRI Based on Federated Learning with YOLOv11
por: Monisha, Sheikh Moonwara Anjum, et al.
Publicado: (2025)

VIBE: Video-Input Brain Encoder for fMRI Response Modeling
por: Schad, Daniel Carlström, et al.
Publicado: (2025)

Ada-FCN: Adaptive Frequency-Coupled Network for fMRI-Based Brain Disorder Classification
por: Xun, Yue, et al.
Publicado: (2025)

MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding
por: Wei, Yuxiang, et al.
Publicado: (2025)

NeuroPictor: Refining fMRI-to-Image Reconstruction via Multi-individual Pretraining and Multi-level Modulation
por: Huo, Jingyang, et al.
Publicado: (2024)

Using Graph Convolutional Networks to Address fMRI Small Data Problems
por: Screven, Thomas, et al.
Publicado: (2025)

Region-Aware Reconstruction Strategy for Pre-training fMRI Foundation Model
por: Doodipala, Ruthwik Reddy, et al.
Publicado: (2025)

Mind-to-Image: Projecting Visual Mental Imagination of the Brain from fMRI
por: Caselles-Dupré, Hugo, et al.
Publicado: (2024)

Leveraging sinusoidal representation networks to predict fMRI signals from EEG
por: Li, Yamin, et al.
Publicado: (2023)

SynBrain: Enhancing Visual-to-fMRI Synthesis via Probabilistic Representation Learning
por: Mai, Weijian, et al.
Publicado: (2025)

On the Relationship Between Double Descent of CNNs and Shape/Texture Bias Under Learning Process
por: Iwase, Shun, et al.
Publicado: (2025)

Generalizable Representation Learning for fMRI-based Neurological Disorder Identification
por: Cui, Wenhui, et al.
Publicado: (2024)

Federated Learning for Video Violence Detection: Complementary Roles of Lightweight CNNs and Vision-Language Models for Energy-Efficient Use
por: Thuau, Sébastien, et al.
Publicado: (2025)

NeuroSwift: A Lightweight Cross-Subject Framework for fMRI Visual Reconstruction of Complex Scenes
por: Zhang, Shiyi, et al.
Publicado: (2025)

Mitigating analytical variability in fMRI results with style transfer
por: Germani, Elodie, et al.
Publicado: (2024)

FreqSelect: Frequency-Aware fMRI-to-Image Reconstruction
por: Ye, Junliang, et al.
Publicado: (2025)

Addressing Data Scarcity in 3D Trauma Detection through Self-Supervised and Semi-Supervised Learning with Vertex Relative Position Encoding
por: Chaudhary, Shivam, et al.
Publicado: (2026)

SelfFed: Self-Supervised Federated Learning for Data Heterogeneity and Label Scarcity in Medical Images
por: Khowaja, Sunder Ali, et al.
Publicado: (2023)

Data-Free Dynamic Compression of CNNs for Tractable Efficiency
por: Meiner, Lukas, et al.
Publicado: (2023)

BrainCast: A Spatio-Temporal Forecasting Model for Whole-Brain fMRI Time Series Prediction
por: Gao, Yunlong, et al.
Publicado: (2026)

Explainable AI for Autism Diagnosis: Identifying Critical Brain Regions Using fMRI Data
por: Vidya, Suryansh, et al.
Publicado: (2024)

Foundation-Model-Boosted Multimodal Learning for fMRI-based Neuropathic Pain Drug Response Prediction
por: Fan, Wenrui, et al.
Publicado: (2025)

A Lightweight Generative Model for Interpretable Subject-level Prediction
por: Mauri, Chiara, et al.
Publicado: (2023)

DeBUGCN -- Detecting Backdoors in CNNs Using Graph Convolutional Networks
por: Vartak, Akash, et al.
Publicado: (2025)

Teaching CORnet Human fMRI Representations for Enhanced Model-Brain Alignment
por: Lu, Zitong, et al.
Publicado: (2024)

On the universality of neural encodings in CNNs
por: Guth, Florentin, et al.
Publicado: (2024)

Understanding CNNs from excitations
por: Ying, Zijian, et al.
Publicado: (2022)

SpaNN: Detecting Multiple Adversarial Patches on CNNs by Spanning Saliency Thresholds
por: Victorica, Mauricio Byrd, et al.
Publicado: (2025)

Reliable Evaluation of Attribution Maps in CNNs: A Perturbation-Based Approach
por: Nieradzik, Lars, et al.
Publicado: (2024)

Cott-ADNet: Lightweight Real-Time Cotton Boll and Flower Detection Under Field Conditions
por: Wang, Rui-Feng, et al.
Publicado: (2025)

VoxelFormer: Parameter-Efficient Multi-Subject Visual Decoding from fMRI
por: Le, Chenqian, et al.
Publicado: (2025)

StableMind: Source-Free Cross-Subject fMRI Decoding with Regularized Adaptation
por: Guo, Jintao, et al.
Publicado: (2026)