0000000001177951

AUTHOR

Ignazio Gallo

E-Fairs: a Cyber-Physical System for Aggregation and Economy of Scale in e-Commerce

In recent years, the e-commerce arena has deeply changed because of the advent of new business models and the growing weight of huge global actors like Amazon. Some business models create competition between users, and the product price tends to rise (e.g., online auctions); other models, including group-buying, make users cooperate, and the price tends to go down. The present study extends the group-buying model and proposes a cyber-physical system called e-fair, in which both sellers and buyers are grouped to negotiate on a specific product or service. E-fairs minimize the global purchase price and the shipping resources respectively with the aggregation of demand and supply as well as or…

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Learning to Navigate in the Gaussian Mixture Surface

In the last years, deep learning models have achieved remarkable generalization capability on computer vision tasks, obtaining excellent results in fine-grained classification problems. Sophisticated approaches based-on discriminative feature learning via patches have been proposed in the literature, boosting the model performances and achieving the state-of-the-art over well-known datasets. Cross-Entropy (CE) loss function is commonly used to enhance the discriminative power of the deep learned features, encouraging the separability between the classes. However, observing the activation map generated by these models in the hidden layer, we realize that many image regions with low discrimin…

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