16 citations · 29 across the 2 of their papers we have counts for
2 papers
cs.CV2023★ 13 cited
Efficient Scopeformer: Towards Scalable and Rich Feature Extraction for Intracranial Hemorrhage Detection
Yassine Barhoumi, Nidhal C. Bouaynaya, Ghulam Rasool
The quality and richness of feature maps extracted by convolution neural networks (CNNs) and vision Transformers (ViTs) directly relate to the robust model performance. In medical…
eess.IV2021★ 16 cited
Scopeformer: n-CNN-ViT Hybrid Model for Intracranial Hemorrhage Classification
Yassine Barhoumi, Ghulam Rasool
We propose a feature generator backbone composed of an ensemble of convolutional neuralnetworks (CNNs) to improve the recently emerging Vision Transformer (ViT) models. We tackled…