Explainable AI model classifies brain tumors from MRI scans with high accuracy
A hybrid TransUNet–DenseNet121 deep learning framework classifies brain tumors from MRI scans with reported accuracies up to 99.56 percent while ...
A hybrid TransUNet–DenseNet121 deep learning framework classifies brain tumors from MRI scans with reported accuracies up to 99.56 percent while ...
A systematic comparison of nine CNN architectures on label-free multimodal microscopy images of colonic tissue found ResNet50 with partial fine-tuning ...
A hybrid deep learning model fusing MobileNetV3, DenseNet121, and DINOv2 achieved up to 99.3% accuracy in classifying five types of ...
A hybrid deep learning framework that fuses handcrafted morphological measurements with convolutional image features identified two destructive root-knot nematode species ...
A new deep learning framework that pairs super-resolution image enhancement with swarm-optimized transfer learning classified Alzheimer's disease stages from MRI ...
A knowledge-distilled MobileNetV2 model classified healthy, early and diseased wheat stripe mosaic virus stages in South African field images, reaching ...
A Chinese research team has developed DeepFusion-HSK, a multimodal deep learning system that distinguishes epithelial from non-epithelial herpes simplex keratitis ...
Researchers in India have built a unified deep learning framework that classifies brain tumors in MRI scans with 98.52 percent ...
Researchers have built a modified dual-task DenseNet121 that classifies brain tumors from MRI scans with over 99 percent accuracy while ...
A machine learning model combining a deep learning signature from spinal X-rays with clinical features accurately predicts short-term structural damage ...
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© 2025 Scienmag - Science Magazine