Results 31 to 40 of about 247,960 (211)
AE-Net: Novel Autoencoder-Based Deep Features for SQL Injection Attack Detection
IEEE Access, 2023 Structured Query Language (SQL) injection attacks represent a critical threat to database-driven applications and systems, exploiting vulnerabilities in input fields to inject malicious SQL code into database queries. This unauthorized access enables attackers to manipulate, retrieve, or even delete sensitive data.
Nisrean Thalji +4 more
openaire +3 more sources
, 2023 Recently, anomaly detection in dynamic networks has received increased attention due to massive network-structured data arising in many fields, such as network security, intelligent transportation systems, and computational biology.
Zhen Zhang +4 more
core +1 more source
Exploring Autoencoder-based Error-bounded Compression for Scientific Data [PDF]
, 2021 Error-bounded lossy compression is becoming an indispensable technique for the success of today\u27s scientific projects with vast volumes of data produced during the simulations or instrument data acquisitions.
Liu, Jinyang +15 more
core +1 more source
An AutoEncoder and LSTM-Based Traffic Flow Prediction Method
Sensors, 2019 Smart cities can effectively improve the quality of urban life. Intelligent Transportation System (ITS) is an important part of smart cities. The accurate and real-time prediction of traffic flow plays an important role in ITSs. To improve the prediction
Wangyang Wei, Honghai Wu, Huadong Ma
doaj +1 more source
Proceedings of the ACM Conference on Health, Inference, and Learning, 2020 Systematic review (SR) is an essential process to identify, evaluate, and summarize the findings of all relevant individual studies concerning health-related questions. However, conducting a SR is labor-intensive, as identifying relevant studies is a daunting process that entails multiple researchers screening thousands of articles for relevance.
Eric Wonhee Lee +3 more
openaire +3 more sources
Sensors, 2023 The prediction of system degradation is very important as it serves as an important basis for the formulation of condition-based maintenance strategies.
Lin Huang, Xin Pan, Yajie Liu, Li Gong
doaj +1 more source
Holographic-(V)AE: an end-to-end SO(3)-Equivariant (Variational) Autoencoder in Fourier Space
Physical Review Research, 2022 Group-equivariant neural networks have emerged as a data-efficient approach to solve classification and regression tasks, while respecting the relevant symmetries of the data. However, little work has been done to extend this paradigm to the unsupervised and generative domains. Here, we present Holographic
Gian Marco Visani +3 more
openaire +4 more sources
JMIR Medical InformaticsBackgroundBy analyzing electronic health record snapshots of similar patients, physicians can proactively predict disease onsets, customize treatment plans, and anticipate patient-specific trajectories.
Deyi Li +5 more
doaj +1 more source
IEEE Access, 2019 Extreme learning machine is characterized by less training parameters, fast training speed, and strong generalization ability. It has been applied to obtain feature representations from the complex data in the tasks of data clustering or classification ...
Hongwei Ge +3 more
doaj +1 more source
Anomaly Detection for Agricultural Vehicles Using Autoencoders
Sensors, 2022 The safe in-field operation of autonomous agricultural vehicles requires detecting all objects that pose a risk of collision. Current vision-based algorithms for object detection and classification are unable to detect unknown classes of objects. In this
Esma Mujkic +4 more
doaj +1 more source