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Anomaly Detection
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In this paper, we study the efficiency of Graph Transformer Network for noisy label propagation in the task of classifying video anomaly actions. Given a weak supervised dataset, our methods focus on improving the quality of generated labels and use the labels for training a video classifier with deep network.
11p
viambani
18-06-2024
1
1
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A deep learning approach combining autoencoder with supervised classifiers for IoT anomaly detection
Anomaly detection for Internet of things (IoT) networks is a challenging issue due to the huge number of devices that connect to each other and generate huge amounts of data. In this study, we propose a model combining Autoencoder (AE) with classification algorithms to build an endto-end architecture for processing, feature extraction and data classification.
13p
viambani
18-06-2024
6
1
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This study is to evaluate the precision of some new global Earth Gravitational Models in the East Vietnam Sea, selecting the best model. The method and the program for calculating Free air gravity anomaly from the global earth gravitational model have been researched and developed. Evaluation of the precision of the models is done by comparing the models with ship-derived gravity anomalies. Data with anomalous signs are detected and removed when the deviation exceeds three times the root mean square deviation.
13p
dianmotminh02
03-05-2024
1
1
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Exome sequencing (ES) is becoming more widely available in prenatal diagnosis. However, data on its clinical utility and integration into clinical management remain limited in practice. Herein, we report our experience implementing prenatal ES (pES) in a large cohort of fetuses with anomalies detected by ultrasonography using a hospital-based in-house multidisciplinary team (MDT) facilitated by a three-step genotype-driven followed by phenotype-driven analysis framework.
20p
viellison
28-03-2024
5
2
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While it is the most common thoracic venous anomaly, a persistent left vena cava superior may present in atypical variations, which are important to consider during clinical management. To the best of our knowledge, this is the first report of a persistent left vena cava superior draining into the left atrial appendage.
6p
vilazada
31-01-2024
3
2
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Oculo-facio-cardio-dental (OFCD) syndrome is a rare condition that affects the eyes, face, heart, and teeth of patients. One notable dental characteristic of OFCD is radiculomegaly, or root gigantism, which highlights the role of dentists in detecting this syndrome. OFCD is an X-linked dominant syndrome that results from a variant in the BCOR gene.
14p
vitiki
30-01-2024
2
2
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Advanced diagnostic systems and screening services for health care have made it possible to improve the detection of congenital cardiovascular abnormalities, including coronary artery variations. Many coronary artery fistulas are congenital, and this can also be reported in patients with normal heart anatomy.
3p
viintuit
26-09-2023
2
0
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The Dempster-Shafer (DS) theory of evidence is frequently used to combine multiple supervised machine learning models into a robust fusion-based model. However, using the DS theory to create a fusion model from multiple one-class classifications (OCCs) for network anomaly detection is a challenging task.
16p
vimulcahy
18-09-2023
5
4
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Ebook Handbook of research on wireless security Part 1 includes contents: Malicious software in mobile devices, Secure service discovery, Security of mobile code, Identity management, Wireless wardriving, Intrusion and anomaly detection in wireless networks, Peer-to-peer (P2P) network security: firewall issues, Identity management for wireless service access, Privacy enhancing techniques: a survey and classification, Vulnerability analysis and defenses in wireless networks,…
448p
haojiubujain06
05-09-2023
11
4
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Malfunctions in Clinical Decision Support (CDS) systems occur due to a multitude of reasons, and often go unnoticed, leading to potentially poor outcomes. Our goal was to identify malfunctions within CDS systems.
10p
visteverogers
24-06-2023
3
1
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To reduce unnecessary redundancy, in this paper, we divide attack detection into two phases, which are anomaly detection phase with lightweight machine learning algorithm and attack detection phase when anomaly behaviors have been detected.
8p
vihawkeye
26-05-2023
8
4
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To evaluate the imaging characteristics of coronary artery fistulas (CAFs) by multidetector computed tomography (MDCT). A prospective descriptivestudy from January 2019 to September 2020 enrolled 31 patients (11 males, mean age 56 years) detected CAFs on MDCT at Radiology Centre of Bach Mai hospital.
6p
vigamora
23-05-2023
3
2
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The objective of this study is to investigate the hotspot (fires and other thermal anomalies) detection and characterization product from the TET-1 satellite sensing system from the German Aerospace Centre (DLR). The satellite is envisioned, as part of a constellation of satellites, to provide detection and characterization of fires at a higher spatial resolution when compared to the current standard global coverage from the MODIS fire products.
112p
runthenight04
02-02-2023
4
2
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This study used the 2D and 3D normalized total gradient (NTG) method of gravity anomalies to detect the gravity anomalies caused by oil-gas reservoirs. The NTG of gravity anomalies can be associated with known oil-gas reservoirs, and most of them seem to be a good coincidence with the reservoirs.
10p
vipagani
24-10-2022
4
2
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Lecture Data mining: Lesson 21. The main topics covered in this chapter include: outlier discovery/anomaly detection; credit card fraud detection; telecommunication fraud detection; network intrusion detection; fault detection;... Please refer to the content of document.
20p
tieuvulinhhoa
22-09-2022
11
3
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In this paper, we propose a novel method for video anomaly detection motivated by an existing architecture for sequence-to-sequence prediction and reconstruction using a spatio-temporal convolutional Long Short-Term Memory (convLSTM).
6p
vigeneralmotors
13-07-2022
688
7
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Recently, latent representation models, such as Shrink Autoencoder (SAE), have been demonstrated as robust feature representations for one-class learning-based network anomaly detection. In these studies, benchmark network datasets that are processed in laboratory environments to make them completely clean are often employed for constructing and evaluating such models.
11p
viirenerosenfeld
26-05-2022
14
3
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A major earthquake (Mw=7.0) occurred in the Samos Island on the 30th of October 2020 at 11:51 UTC. Swarm satellite magnetic data were analysed for 153 days before and 46 days after the earthquake. Preearthquake and postearthquake anomaly search is constrained within the Dobrovolsky’s Circular Area. Fundamentally, there are 5 steps for processing satellite magnetic data to interpret the earthquake preparation phase. The first step is converting geographical coordinates to geomagnetic latitude and longitude.
10p
tanmocphong
29-01-2022
11
0
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The tectonic and structural properties of Erzurum and its surroundings have been investigated by evaluating the seismotectonic b - value, magnetic anomaly, edge detection analysis (total horizontal derivative (THDR) and tilt angle (TA)), Curie Point Depth (CPD), P-wave velocity (Vp), and Vp / Vs (S - wave velocity) ratio and by imaging the regional distributions of these parameters. For this purpose, all parameters have been combined to be able to reveal the new useful results on the study region and are presented for different locations and depths.
24p
tanmocphong
29-01-2022
23
2
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The problem of finding anomalies and outliers in datasets is one of the most important challenges of modern data analysis. Among the commonly dedicated tools to solve this task one can find Isolation Forest (IF) that is an efficient, conceptually simple, and fast method.
17p
guernsey
28-12-2021
12
0
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