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Found 5 papers, 2 papers with code
The revenge of BiSeNet: Efficient Multi-Task Image Segmentation
Recent advancements in image segmentation have focused on enhancing the efficiency of the models to meet the demands of real-time applications, especially on edge devices.
PEM: Prototype-based Efficient MaskFormer for Image Segmentation
To fill this gap, we propose Prototype-based Efficient MaskFormer (PEM), an efficient transformer-based architecture that can operate in multiple segmentation tasks.
Entropic Score metric: Decoupling Topology and Size in Training-free NAS
Neural Networks design is a complex and often daunting task, particularly for resource-constrained scenarios typical of mobile-sized models.
FreeREA: Training-Free Evolution-based Architecture Search
In the last decade, most research in Machine Learning contributed to the improvement of existing models, with the aim of increasing the performance of neural networks for the solution of a variety of different tasks.
Fault-Aware Design and Training to Enhance DNNs Reliability with Zero-Overhead
Deep Neural Networks (DNNs) enable a wide series of technological advancements, ranging from clinical imaging, to predictive industrial maintenance and autonomous driving.
