1 code implementation • 27 May 2024 • Md Mostafijur Rahman, Mustafa Munir, Debesh Jha, Ulas Bagci, Radu Marculescu
To this end, we utilize variable perturbed bounding box prompts (BBP) to enrich the learning context and enhance the model's robustness to BBP perturbations during inference.
1 code implementation • 11 May 2024 • Md Mostafijur Rahman, Mustafa Munir, Radu Marculescu
An efficient and effective decoding mechanism is crucial in medical image segmentation, especially in scenarios with limited computational resources.
1 code implementation • 10 May 2024 • Mustafa Munir, William Avery, Md Mostafijur Rahman, Radu Marculescu
Our smallest model, GreedyViG-S, achieves 81. 1% top-1 accuracy on ImageNet-1K, 2. 9% higher than Vision GNN and 2. 2% higher than Vision HyperGraph Neural Network (ViHGNN), with less GMACs and a similar number of parameters.
1 code implementation • 1 Jul 2023 • Mustafa Munir, William Avery, Radu Marculescu
Our work proves that well designed hybrid CNN-GNN architectures can be a new avenue of exploration for designing models that are extremely fast and accurate on mobile devices.