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Local Novelty Detection in Multi-class Recognition Problems
2015
2015 IEEE Winter Conference on Applications of Computer Vision
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With our local novelty detection approach, we achieve state-of-the-art performance in multi-class novelty detection on two popular visual object recognition datasets, Caltech-256 and ImageNet. ...
In this paper, we propose using local learning for multiclass novelty detection, a framework that we call local novelty detection. ...
Experimental results for novel visual object detection in object recognition as well as for the specific applications of novel face detection and unknown bird species detection are presented in Sect. 4 ...
doi:10.1109/wacv.2015.113
dblp:conf/wacv/BodesheimFRD15
fatcat:luckbbi4gndirirjutddazqmsy
Kernel Null Space Methods for Novelty Detection
2013
2013 IEEE Conference on Computer Vision and Pattern Recognition
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Detecting samples from previously unknown classes is a crucial task in object recognition, especially when dealing with real-world applications where the closed-world assumption does not hold. ...
Beside the possibility of modeling a single class, we are able to treat multiple known classes jointly and to detect novelties for a set of classes with a single model. ...
Identifying samples from currently unknown classes is hence an essential step in visual object recognition. ...
doi:10.1109/cvpr.2013.433
dblp:conf/cvpr/BodesheimFRKD13
fatcat:ntfashyxvbdx5kif2mzuh73oay
Automatically Discovering Properties That Specify the Latent Behavior of UML Models
[chapter]
2010
Lecture Notes in Computer Science
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In contrast, this paper proposes an automated approach to generating temporal logic properties that specify the latent behavior of existing UML models; these are unknown properties exhibited by the system ...
The Marple-discovered properties can be used to refine the models to either remove unwanted behavior or to explicitly document a desirable property as required system behavior. ...
While in previous work novelty search was used to discover better solutions than other evolutionary computation techniques, in this paper, we use novelty search to discover a suite of properties that cumulatively ...
doi:10.1007/978-3-642-16145-2_22
fatcat:bd5vampdjjdndikpwa763lliku
Vision-Based Novelty Detection Using Deep Features and Evolved Novelty Filters for Specific Robotic Exploration and Inspection Tasks
2019
Sensors
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The proposed framework presented high-novelty detection accuracy with competitive or even better results than the baseline methods. ...
In this work, we propose a visual novelty detection framework for specific exploration and inspection tasks based on evolved novelty detectors. ...
In general, the novelty detection methods construct a model with the examples of the normal class and use this model with unknown data to compute novelties. ...
doi:10.3390/s19132965
fatcat:srzvv426mbfbzjxypxgej3dusm
Digits that are not: Generating new types through deep neural nets
[article]
2016
arXiv
pre-print
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propose a notion of knowledge-driven creativity that circumvent the need for an externally imposed value function, allowing the system to explore based on what it has learned from a set of referential objects ...
For an artificial creative agent, an essential driver of the search for novelty is a value function which is often provided by the system designer or users. ...
x), or novelty (or outlier) detection (where the goal is to detect objects from a stream which do not look like objects in D by thresholding p(x)). ...
arXiv:1606.04345v1
fatcat:7rg3nbqyarbsrldl6uvwloatim
Visualizing Image Content to Explain Novel Image Discovery
[article]
2019
arXiv
pre-print
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We focus on the goal of detecting observations with novel content, which can alert us to artifacts in the data set or, potentially, the discovery of previously unknown phenomena. ...
To aid in interpreting and diagnosing the novel aspect of these selected observations, we recommend the use of novelty detection methods that generate explanations. ...
Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. ...
arXiv:1908.05006v1
fatcat:flaadp62fjc47a2strwtv5tjo4
Fractal Analogies for General Intelligence
[chapter]
2012
Lecture Notes in Computer Science
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In the second, we describe how the fractal technique enables the percept-to-action mapping in a simple, simulated world. ...
In the first part, we describe a technique of fractal analogies and show how it gives human-level performance on an intelligence test called the Odd One Out. ...
Markou & Singh [20] [21] review statistical and neural network techniques for novelty detection. Neto & Nehmzow [24] illustrate the use of visual novelty detection in autonomous robots. ...
doi:10.1007/978-3-642-35506-6_19
fatcat:ukklrgokjrhafaikx4s6635obm
Exploration strategies for incremental learning of object-based visual saliency
2015
2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)
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In order to get a better and faster learning, we use intrinsic motivation to drive our observation selection, based on uncertainty and novelty detection. ...
Searching for objects in an indoor environment can be drastically improved if a task-specific visual saliency is available. ...
The selection of target is often obtained with a saliency map, but also by novelty detection [12] , reinforcement learning techniques [15] , or in very simple configuration, competence progress [1] ...
doi:10.1109/devlrn.2015.7346099
dblp:conf/icdl-epirob/CrayeFG15
fatcat:qchxd22e3bfqdkqb2i7i7o56bq
A technique to detect periodic and non-periodic ultra-rapid flux time variations with standard radio-astronomical data
2018
Journal of astrophysics and astronomy
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2018 pre-print arXiv:1804.09239v1 fatcat:vhutga5pwzec7ag5ldeakoibdm
Another advantage is that it allows a direct visualization of the shape of the signals, while it is difficult to see the shape with a Fourier transform. ...
Another major novelty of our work is that we use electric fields taken in a standard format with standard instrumentation at a radio observatory and therefore no specialized instrumentation is needed. ...
Since then,33 objects with The autocorrelation will not be advantageous over conventional matched-filtering techniques for detecting periodic repeating bursts, particularly if these conventional techniques ...
doi:10.1007/s12036-018-9525-6
fatcat:23ebsnosdbbazjgsy7sebmtuby
Motivation Learning in Mind Model CAM
2015
International Journal of Intelligence Science
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Introspective search can perform novelty detection to discover novel events. ...
and unknown object information during testing. ...
doi:10.4236/ijis.2015.52006
fatcat:nklrdhakjba7dbmehienri2cc4
An Analysis of Outlier Detection through clustering method
2020
International Journal of Advanced engineering Management and Science
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This research paper deals with an outlier which is known as an unusual behavior of any substance present in the spot. ...
This is a detection process that can be employed for both anomaly detection and abnormal observation. This can be obtained through other members who belong to that data set. ...
INTRODUCTION Mining, in general, is termed as the intrinsic methodology of discovering interesting, formerly unknown data patterns. ...
doi:10.22161/ijaems.612.13
fatcat:w7c55r4y2fdvrndhx7lelwrtaa
Vision based, statistical learning system for fault recognition in industrial assembly environment
2016
2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA)
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The paper presents a statistical learning system based visual solution developed and applied for fault detection in industrial environment. ...
The developed system is able to detect faults with the size of 2% of the total picture based on previously learned models. ...
tasks: it has to detect the object from motion information, collect frame pictures from it, separate the object from the background, find the statistically most corresponding model with comparing the object ...
doi:10.1109/etfa.2016.7733730
dblp:conf/etfa/ViharosCHSBZPSK16
fatcat:nfqkmtka4nfe7ohrvads543ikm
Novelty detection: a review—part 1: statistical approaches
2003
Signal Processing
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Novelty detection is the identification of new or unknown data or signal that a machine learning system is not aware of during training. ...
Novelty detection is one of the fundamental requirements of a good classification or identification system since sometimes the test data contains information about objects that were not known at the time ...
Conclusion In this paper we have presented a survey of novelty detection using statistical approaches. ...
doi:10.1016/j.sigpro.2003.07.018
fatcat:7lbpn2wrrnfprim3bd7ah45i5u
Analyzing change in spatial data by utilizing polygon models
2010
Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application - COM.Geo '10
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We evaluate our framework in case studies that center on ozone pollution monitoring, and on diagnosing glaucoma from visual field analysis. ...
In this paper, we present a framework for the detection and analysis of patterns of change; the framework analyzes change by comparing sets of polygons. ...
In contrast, our work is applicable for data with unknown object identity and for datasets that contain numerical attributes. ...
doi:10.1145/1823854.1823880
dblp:conf/comgeo/RinsurongkawongCET10
fatcat:zdtza4rbp5bghojqnarmacfoti
Data Mining in Education : A Review on the Knowledge Discovery Perspective
2014
International Journal of Data Mining & Knowledge Management Process
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In this paper, we have reviewed Knowledge Discovery perspective in Data Mining and consolidated different areas of data mining, its techniques and methods in it. ...
patterns may then be converted into knowledge.Data mining is the process of extracting the information and patterns derived by the KDD process which helps in crucial decision-making.Data mining works with ...
data mining tools are DBMiner, Clementine, Intelligent Miner, RapidMiner and Weka etc [11] .DM combines machine learning, statistics and visualization techniques to discover and extract knowledge. ...
doi:10.5121/ijdkp.2014.4504
fatcat:5wldcmrngvgojhnwbb5nafze4a
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