Search results for "Novelty detection"
showing 9 items of 9 documents
Stimulus-induced gamma activity in the electrocorticogram of freely moving rats: the neuronal signature of novelty detection.
2009
To investigate the cortical activity pattern associated with the exploration and identification of a novel object we recorded the intracranial electrocorticogram (ECoG) in the barrel cortex of freely moving adult rats using wireless technology. We report here that the exploration and detection of a novel object correlate with a transient increase of synchronized oscillatory activity in the 40–47 Hz frequency band. This specific cortical activity pattern occurs 200–300 ms after the first sensory contact with the novel stimulus and decreases in power in the subsequent recording sessions with the same object. During the first explorative session the increase in 40–47 Hz is associated with a si…
Musical Feature and Novelty Curve Characterizations as Predictors of Segmentation Accuracy
2017
Novelty detection is a well-established method for analyzing the structure of music based on acoustic descriptors. Work on novelty-based segmentation prediction has mainly concentrated on enhancement of features and similarity matrices, novelty kernel computation and peak detection. Less attention, however, has been paid to characteristics of musical features and novelty curves, and their contribution to segmentation accuracy. This is particularly important as it can help unearth acoustic cues prompting perceptual segmentation and find new determinants of segmentation model performance. This study focused on spectral, rhythmic and harmonic prediction of perceptual segmentation density, whic…
An unsupervised Learning Algorithm for Fatigue Crack Detection in Waveguides
2009
Ultrasonic guided waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges, and high sensitivity to small flaws. This paper describes an SHM method based on UGWs and outlier analysis devoted to the detection and quantification of fatigue cracks in structural waveguides. The method combines the advantages of UGWs with the outcomes of the discrete wavelet transform (DWT) to extract defect-sensitive features aimed at performing a multivariate diagnosis of damage. In particular, the DWT is exploited to generate a set of relevant wavelet coefficients to construct a uni-dimensional or multi-di…
Measuring the Novelty of Natural Language Text Using the Conjunctive Clauses of a Tsetlin Machine Text Classifier
2020
Most supervised text classification approaches assume a closed world, counting on all classes being present in the data at training time. This assumption can lead to unpredictable behaviour during operation, whenever novel, previously unseen, classes appear. Although deep learning-based methods have recently been used for novelty detection, they are challenging to interpret due to their black-box nature. This paper addresses \emph{interpretable} open-world text classification, where the trained classifier must deal with novel classes during operation. To this end, we extend the recently introduced Tsetlin machine (TM) with a novelty scoring mechanism. The mechanism uses the conjunctive clau…
Modelling and prediction of perceptual segmentation
2017
While listening to music, we somehow make sense of a multiplicity of auditory events; for example, in popular music we are often able to recognize whether the current section is a verse or a chorus, and to identify the boundaries between these segments. This organization occurs at multiple levels, since we can discern motifs, phrases, sections and other groupings. In this work, we understand segment boundaries as instants of significant change. Several studies on music perception and cognition have strived to understand what types of changes are associated with perceptual structure. However, effects of musical training, possible differences between real-time and non real-time segmentation, and…
The on-line curvilinear component analysis (onCCA) for real-time data reduction
2015
Real time pattern recognition applications often deal with high dimensional data, which require a data reduction step which is only performed offline. However, this loses the possibility of adaption to a changing environment. This is also true for other applications different from pattern recognition, like data visualization for input inspection. Only linear projections, like the principal component analysis, can work in real time by using iterative algorithms while all known nonlinear techniques cannot be implemented in such a way and actually always work on the whole database at each epoch. Among these nonlinear tools, the Curvilinear Component Analysis (CCA), which is a non-convex techni…
Interaction features for prediction of perceptual segmentation:Effects of musicianship and experimental task
2016
As music unfolds in time, structure is recognised and understood by listeners, regardless of their level of musical expertise. A number of studies have found spectral and tonal changes to quite successfully model boundaries between structural sections. However, the effects of musical expertise and experimental task on computational modelling of structure are not yet well understood. These issues need to be addressed to better understand how listeners perceive the structure of music and to improve automatic segmentation algorithms. In this study, computational prediction of segmentation by listeners was investigated for six musical stimuli via a real-time task and an annotation (non real-tim…
Panel Summary Perceptual Learning and Discovering
1994
The problem of learning and discovering in perception is addressed and discussed with particular reference to present machine learning paradigms. These paradigms are briefly introduced by S. Gaglio. The subsymbolic approach is addressed by S. Nolfi, and the role of symbolic learning is analysed by F. Esposito. Many of the open problems, that are evidentiated in the course of the panel, show how this is an important field of research that still needs a lot of investigation. In particular, as a result of the whole discussion, it seems that a suitable integration of different approaches must be accurately investigated. It is observed, in fact, that the weakness of the most part of the existing…
Contribution à la caractérisation de la mémoire des aliments
2008
Memory plays a fundamental role in the acquisition of food likes and dislikes. As a consequence, a better understanding food memory will contribute to a better understanding food choice and behavior. This work sets out several experiments based on a common recognition paradigm: during a first session, participants are exposed to the food to be remembered (target) under conditions ensuring incidental learning. After a certain retention interval, participants are asked to recognize the target among a set of distractors with a flavor and/or a texture slightly different from the target. In line with previous works on food memory, three main results emerged from this work. First, participants of…