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Found 3 papers, 1 papers with code
Toward a Realistic Benchmark for Out-of-Distribution Detection
Deep neural networks are increasingly used in a wide range of technologies and services, but remain highly susceptible to out-of-distribution (OOD) samples, that is, drawn from a different distribution than the original training set.
HOLMES: HOLonym-MEronym based Semantic inspection for Convolutional Image Classifiers
Convolutional Neural Networks (CNNs) are nowadays the model of choice in Computer Vision, thanks to their ability to automatize the feature extraction process in visual tasks.
Object Tracking through Residual and Dense LSTMs
Visual object tracking task is constantly gaining importance in several fields of application as traffic monitoring, robotics, and surveillance, to name a few.
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