Tag: Grad-CAM

Researchers have built a modified dual-task DenseNet121 that classifies brain tumors from MRI scans with over 99 percent accuracy while ...

Researchers built ViTDrone, a Vision Transformer framework that simultaneously steers a drone through corridors and detects collisions while using Grad-CAM ...

A convolutional neural network trained with transfer learning can identify angiographic patterns of cystoid macular edema in retinal vasculitis patients, ...

Researchers have built SpudNet5-R3, a lightweight explainable convolutional neural network that detects potato early and late blight with up to ...

Tanzanian researchers trained deep neural networks to classify nitrogen status in maize leaves from smartphone photos, achieving over 93 percent ...

An Indian research team has developed GraphX, an explainable graph transformer framework that classifies nail diseases with 94.97 percent accuracy ...

A multimodal deep learning model that combines panoramic dental X-rays with structured patient metadata significantly outperforms image-only or metadata-only approaches ...

Researchers have unveiled an explainable deep learning framework that detects insect crop pests in real time with up to 98 ...

Researchers have built a hybrid transformer-U-Net that segments diabetic foot ulcers with expert-level overlap and quantitatively explainable visualisations.

Researchers in India report that a hybrid ADAMW plus SGD optimizer with embedded feature selection boosts deep learning accuracy for ...