[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

O'Shea et al., 2017 - Google Patents

Learning robust general radio signal detection using computer vision methods

O'Shea et al., 2017

Document ID
3854168682865736322
Author
O'Shea T
Roy T
Clancy T
Publication year
Publication venue
2017 51st asilomar conference on signals, systems, and computers

External Links

Snippet

We introduce a new method for radio signal detection and localization within the time- frequency spectrum based on the use of convolutional neural networks for bounding box regression. Recently, this class of approach has surpassed human-level performance on …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6279Classification techniques relating to the number of classes
    • G06K9/6284Single class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6256Obtaining sets of training patterns; Bootstrap methods, e.g. bagging, boosting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00771Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00496Recognising patterns in signals and combinations thereof

Similar Documents

Publication Publication Date Title
O'Shea et al. Learning robust general radio signal detection using computer vision methods
US20240104386A1 (en) Radio signal identification, identification system learning, and identifier deployment
Basak et al. Combined RF-based drone detection and classification
Oyedare et al. Estimating the required training dataset size for transmitter classification using deep learning
Malof et al. A large-scale multi-institutional evaluation of advanced discrimination algorithms for buried threat detection in ground penetrating radar
US11630996B1 (en) Spectral detection and localization of radio events with learned convolutional neural features
US10621506B2 (en) Apparatus and method for activity detection and classification from sensor data
Katzir et al. Detecting adversarial perturbations through spatial behavior in activation spaces
Li et al. A deep convolutional network for multitype signal detection and classification in spectrogram
Tao et al. Distribution preserving backdoor attack in self-supervised learning
Nguyen et al. Wideband, real-time spectro-temporal RF identification
Zhai et al. A new sense-through-foliage target recognition method based on hybrid differential evolution and self-adaptive particle swarm optimization-based support vector machine
Ristea et al. Estimating the magnitude and phase of automotive radar signals under multiple interference sources with fully convolutional networks
Xu et al. Identification of communication signals using learning approaches for cognitive radio applications
Rayavarapu et al. NLOS identification and mitigation in UWB positioning with bagging-based ensembled classifiers
Zhu et al. Automatic target recognition of synthetic aperture radar images via Gaussian mixture modeling of target outlines
Quezada-Gaibor et al. Surimi: Supervised radio map augmentation with deep learning and a generative adversarial network for fingerprint-based indoor positioning
Caforio et al. Leveraging grad-cam to improve the accuracy of network intrusion detection systems
Huynh-The et al. Accurate deep CNN-based waveform recognition for intelligent radar systems
Khan et al. Deep learning of CSI for efficient device-free human activity recognition
Jiang et al. A novel recognition system for human activity based on wavelet packet and support vector machine optimized by improved adaptive genetic algorithm
Parihar et al. Variational mode decomposition of seismic signals for detection of moving elephants
Liu et al. UniFi: A Unified Framework for Generalizable Gesture Recognition with Wi-Fi Signals Using Consistency-guided Multi-View Networks
Jin Theory on structure and coloring of maximal planar graphs (4)-operations and Kempe equivalent classes
Esmaeilpour et al. From environmental sound representation to robustness of 2D CNN models against adversarial attacks