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Found 4 papers, 1 papers with code
You are what you eat? Feeding foundation models a regionally diverse food dataset of World Wide Dishes
We find that these models generally do not produce quality text and image outputs of dishes specific to different regions.
Analog In-Memory Computing with Uncertainty Quantification for Efficient Edge-based Medical Imaging Segmentation
This work investigates the role of the emerging Analog In-memory computing (AIMC) paradigm in enabling Medical AI analysis and improving the certainty of these models at the edge.
Genetic Algorithm enhanced by Deep Reinforcement Learning in parent selection mechanism and mutation : Minimizing makespan in permutation flow shop scheduling problems
At each generation, the RL agent's action is determining the selection method, the probability of the parent selection and the probability of the offspring mutation.
Skip Connections in Spiking Neural Networks: An Analysis of Their Effect on Network Training
Spiking neural networks (SNNs) have gained attention as a promising alternative to traditional artificial neural networks (ANNs) due to their potential for energy efficiency and their ability to model spiking behavior in biological systems.
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