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DeepSeqSLAM: A Trainable CNN+RNN for Joint Global Description and Sequence-based Place Recognition
MarvinChancán, MichaelMilford....
Published date-11/17/2020
AutonomousDriving, AutonomousVehicles, ImageRetrieval, RobotNavigation, Self-DrivingCars, SimultaneousLocalizationandMapping, VisualLocalization, VisualNavigation, VisualPlaceRecognition
Sequence-based place recognition methods for all-weather navigation are well-known for producing state-of-the-art results under challenging day-night or summer-winter transitions. These systems, however, rely on complex handcrafted heuristics for sequential matching …
Automatic selection of clustering algorithms using supervised graph embedding
NoyCohen-Shapira, LiorRokach....
Published date-11/16/2020
AutoML, Clustering, GraphEmbedding, Meta-Learning
The widespread adoption of machine learning (ML) techniques and the extensive expertise required to apply them have led to increased interest in automated ML solutions that reduce the need for …
Datasets and Models for Authorship Attribution on Italian Personal Writings
GaetanaRuggiero, AlbertGatt, MalvinaNissim....
Published date-11/16/2020
Existing research on Authorship Attribution (AA) focuses on texts for which a lot of data is available (e.g novels), mainly in English. We approach AA via Authorship Verification on short …
Combining GANs and AutoEncoders for Efficient Anomaly Detection
FabioCarrara, GiuseppeAmato, LucaBrombin....
Published date-11/16/2020
AdversarialAttack, AnomalyDetection, ImageClassification, UnsupervisedAnomalyDetection
In this work, we propose CBiGAN -- a novel method for anomaly detection in images, where a consistency constraint is introduced as a regularization term in both the encoder and …
Hierarchical clustering in particle physics through reinforcement learning
JohannBrehmer, SebastianMacaluso, DuccioPappadopulo....
Published date-11/16/2020
Clustering
Particle physics experiments often require the reconstruction of decay patterns through a hierarchical clustering of the observed final-state particles. We show that this task can be phrased as a Markov …
Overcomplete Deep Subspace Clustering Networks
JeyaMariaJoseValanarasu, VishalM.Patel....
Published date-11/16/2020
Clustering
Deep Subspace Clustering Networks (DSC) provide an efficient solution to the problem of unsupervised subspace clustering by using an undercomplete deep auto-encoder with a fully-connected layer to exploit the self …