Latest Research in Image and Video Processing
17 research papers · 2026 median publication year
Top Research Topics in Image and Video Processing
- Brain Tumor Detection and Classification — 10 papers
- Computer Vision and Pattern Recognition — 3 papers
- Image and Video Processing — 2 papers
- Glioma Diagnosis and Treatment — 1 papers
- Meningioma and schwannoma management — 1 papers
Highest-Cited Papers
- The Gate Does Not Choose: An Expert-Initialised Mixture-of-Experts Outperforms Training-Free Consensus under the Official BraTS-2023 Metrics
- A Hybrid Gabor–ViT Embedding with Gated Mamba Deep Learning Framework for Brain Tumor MRI Classification
- Classification of Brain MRI Images with Vision Transformer: Improving Performance with New Layers and Parameter Optimization
- A controlled benchmark of CNN architectures for MRI-based brain tumor detection: Custom networks and transfer learning versus Vision Transformer baselines under a unified image-processing pipeline
- SERA-Net: Rethinking CNN Design for Brain Tumor Classification via Squeeze-and-Excite Attention and Residual Learning
- Automated multi-class wound assessment using dedicated instance segmentation models for boundary detection and classification
- Simple, Safe, and Overlooked: Reclaiming Sustainable Domain Generalization with Statistical Color Matching
- Scale-Aware 3D Deep Learning for Robust Brain Metastasis Detection in Multimodal MRI
- Deep Learning for Automated Detection and Segmentation of Meningioma on Multiparametric MRI
- WICA-Net-M: MRI-Based Brain Tumour Classification Using a Lightweight Wavelet-Integrated Coordinate Attention Network with Frequency-Aware Learning
- ORB-SVM : An Innovative Hybrid Framework for Efficient Brain Tumor Detection from MRI Scans
- Democratizing Neuro-Oncology: Real-Time Multi-Class Brain Tumor Localization in MRI Using YOLOv11 for Early Intervention
- FIBONACCINET: A BIOLOGICALLY-INSPIRED DEEP LEARNING ARCHITECTURE FOR ACCURATE AND EXPLAINABLE BRAIN TUMOR CLASSIFICATION FROM MRI
- Democratizing Neuro-Oncology: Real-Time Multi-Class Brain Tumor Localization in MRI Using YOLOv11 for Early Intervention
- An adaptive hierarchical class-aware deep ensemble strategy for robust brain tumor classification
- Superfast prediction of brain tumours through adaptive incremental pre-training and re-training through transfer learning using state-of-the-art ResNet18 architectural model
- CRS-Bench: A Reference-Relative Reliability Benchmark for Medical Image Encoders