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Brain Tumor Classification
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Transfer Learning and Explainable AI for Brain Tumor Classification: A Study Using MRI Data from Bangladesh
MediAug: Exploring Visual Augmentation in Medical Imaging
Fibonacci-Net: A Lightweight CNN model for Automatic Brain Tumor Classification
Efficient Brain Tumor Classification with Lightweight CNN Architecture: A Novel Approach
Transfer Learning Strategies for Pathological Foundation Models: A Systematic Evaluation in Brain Tumor Classification
Enhancing Transfer Learning for Medical Image Classification with SMOTE: A Comparative Study
SKIPNet: Spatial Attention Skip Connections for Enhanced Brain Tumor Classification
An Ensemble Approach for Brain Tumor Segmentation and Synthesis
Comparative Analysis of Resource-Efficient CNN Architectures for Brain Tumor Classification
Residual Vision Transformer (ResViT) Based Self-Supervised Learning Model for Brain Tumor Classification
Edge-Enhanced Dilated Residual Attention Network for Multimodal Medical Image Fusion
Enhancing Brain Tumor Classification Using TrAdaBoost and Multi-Classifier Deep Learning Approaches
Advancing Efficient Brain Tumor Multi-Class Classification -- New Insights from the Vision Mamba Model in Transfer Learning
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decomposition
Brain Tumor Classification on MRI in Light of Molecular Markers
FedBrain-Distill: Communication-Efficient Federated Brain Tumor Classification Using Ensemble Knowledge Distillation on Non-IID Data
Pediatric brain tumor classification using digital histopathology and deep learning: evaluation of SOTA methods on a multi-center Swedish cohort
Deep Learning in Medical Image Classification from MRI-based Brain Tumor Images
Brain Tumor Classification From MRI Images Using Machine Learning
Deep Fusion Model for Brain Tumor Classification Using Fine-Grained Gradient Preservation
Brain Tumor Classification using Vision Transformer with Selective Cross-Attention Mechanism and Feature Calibration
MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor Classification
A Deep Learning Approach for Brain Tumor Classification and Segmentation Using a Multiscale Convolutional Neural Network
Streamlining Brain Tumor Classification with Custom Transfer Learning in MRI Images
Generating 3D Brain Tumor Regions in MRI using Vector-Quantization Generative Adversarial Networks
Optimizing Brain Tumor Classification: A Comprehensive Study on Transfer Learning and Imbalance Handling in Deep Learning Models
Feature Imitating Networks Enhance The Performance, Reliability And Speed Of Deep Learning On Biomedical Image Processing Tasks
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching
An Optimized Ensemble Deep Learning Model For Brain Tumor Classification
Brain Tumor Segmentation from MRI Images using Deep Learning Techniques
Brain Tumor classification and Segmentation using Deep Learning
MProtoNet: A Case-Based Interpretable Model for Brain Tumor Classification with 3D Multi-parametric Magnetic Resonance Imaging
Multi-limb Split Learning for Tumor Classification on Vertically Distributed Data
Hybrid Model using Feature Extraction and Non-linear SVM for Brain Tumor Classification
Brain Tumor MRI Classification using a Novel Deep Residual and Regional CNN
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