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Found 8 papers, 2 papers with code
U-DIADS-Bib: a full and few-shot pixel-precise dataset for document layout analysis of ancient manuscripts
Document Layout Analysis, which is the task of identifying different semantic regions inside of a document page, is a subject of great interest for both computer scientists and humanities scholars as it represents a fundamental step towards further analysis tasks for the former and a powerful tool to improve and facilitate the study of the documents for the latter.
Efficient few-shot learning for pixel-precise handwritten document layout analysis
Layout analysis is a task of uttermost importance in ancient handwritten document analysis and represents a fundamental step toward the simplification of subsequent tasks such as optical character recognition and automatic transcription.
Masked Transformer for image Anomaly Localization
Image anomaly detection consists in detecting images or image portions that are visually different from the majority of the samples in a dataset.
Drone swarm patrolling with uneven coverage requirements
The paper first defines a proper learning model for a single drone, and then extends it to the case of multiple drones both with greedy and cooperative strategies.
VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization
We present a transformer-based image anomaly detection and localization network.
Ranked #9 on
Anomaly Detection
on BTAD
(using extra training data)
Image Anomaly Detection by Aggregating Deep Pyramidal Representations
Anomaly detection consists in identifying, within a dataset, those samples that significantly differ from the majority of the data, representing the normal class.
Image anomaly detection with capsule networks and imbalanced datasets
Image anomaly detection consists in finding images with anomalous, unusual patterns with respect to a set of normal data.
The UMCD Dataset
In recent years, the technological improvements of low-cost small-scale Unmanned Aerial Vehicles (UAVs) are promoting an ever-increasing use of them in different tasks.
