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20122024
most citedObject Detection in Aerial Images: A Large-Scale Benchmark and Challenges

665 citations · 1.3k across the 35 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.LG2022

Geolocation of Cultural Heritage using Multi-View Knowledge Graph Embedding

Hebatallah A. Mohamed, Sebastiano Vascon, Feliks Hibraj +4

Knowledge Graphs (KGs) have proven to be a reliable way of structuring data. They can provide a rich source of contextual information about cultural heritage collections. However,…

cs.LG2022★ 148 cited

Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning

Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis +7

The success of machine learning is fueled by the increasing availability of computing power and large training datasets. The training data is used to learn new models or update exi…

cs.CV2022

The Group Loss++: A deeper look into group loss for deep metric learning

Ismail Elezi, Jenny Seidenschwarz, Laurin Wagner +4

Deep metric learning has yielded impressive results in tasks such as clustering and image retrieval by leveraging neural networks to obtain highly discriminative feature embeddings…

cs.CR2022★ 34 cited

Machine Learning Security against Data Poisoning: Are We There Yet?

Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis +3

The recent success of machine learning (ML) has been fueled by the increasing availability of computing power and large amounts of data in many different applications. However, the…

cs.CV2022★ 1 cited

Relaxation Labeling Meets GANs: Solving Jigsaw Puzzles with Missing Borders

Marina Khoroshiltseva, Arianna Traviglia, Marcello Pelillo +1

This paper proposes JiGAN, a GAN-based method for solving Jigsaw puzzles with eroded or missing borders. Missing borders is a common real-world situation, for example, when dealing…

cs.CR2022

Energy-Latency Attacks via Sponge Poisoning

Antonio Emanuele Cinà, Ambra Demontis, Battista Biggio +2

Sponge examples are test-time inputs optimized to increase energy consumption and prediction latency of deep networks deployed on hardware accelerators. By increasing the fraction…