Search results for "Pattern recognition"
showing 10 items of 2301 documents
Corresponding-pair procedure: a new approach to simulation of dichromatic color perception.
2004
The dichromatic color appearance of a chromatic stimulus T can be described if a stimulus S is found that verifies that a normal observer experiences the same sensation viewing S as a dichromat viewing T. If dichromatic and normal versions of the same color vision model are available, S can be computed by applying the inverse of the normal model to the descriptors of T obtained with the dichromatic model. We give analytical form to this algorithm, which we call the corresponding-pair procedure. The analytical form highlights the requisites that a color vision model must verify for this procedure to be used. To show the capabilities of the method, we apply the algorithm to different color vi…
A measure of concurrent neural firing activity based on mutual information
2020
AbstractMultiple methods have been developed in an attempt to quantify stimulus-induced neural coordination and to understand internal coordination of neuronal responses by examining the synchronization phenomena in neural discharge patterns. In this work we propose a novel approach to estimate the degree of concomitant firing between two neural units, based on a modified form of mutual information (MI) applied to a two-state representation of the firing activity. The binary profile of each single unit unfolds its discharge activity in time by decomposition into the state of neural quiescence/low activity and state of moderate firing/bursting. Then, the MI computed between the two binary st…
A Fuzzy Logic C-Means Clustering Algorithm to Enhance Microcalcifications Clusters in Digital Mammograms
2011
The detection of microcalcifications is a hard task, since they are quite small and often poorly contrasted against the background of images. The Computer Aided Detection (CAD) systems could be very useful for breast cancer control. In this paper, we report a method to enhance microcalcifications cluster in digital mammograms. A Fuzzy Logic clustering algorithm with a set of features is used for clustering microcalcifications. The method described was tested on simulated clusters of microcalcifications, so that the location of the cluster within the breast and the exact number of microcalcifications is known.
3D segmentation of abdominal aorta from CT-scan and MR images
2012
International audience; We designed a generic method for segmenting the aneurismal sac of an abdominal aortic aneurysm (AAA) both from multi-slice MR and CT-scan examinations. It is a semi-automatic method requiring little human intervention and based on graph cut theory to segment the lumen interface and the aortic wall of AAAs. Our segmentation method works independently on MRI and CT-scan volumes and has been tested on a 44 patient dataset and 10 synthetic images. Segmentation and maximum diameter estimation were compared to manual tracing from 4 experts. An inter-observer study was performed in order to measure the variability range of a human observer. Based on three metrics (the maxim…
FPGA implementation of a deep learning algorithm for real-time signal reconstruction in particle detectors under high pile-up conditions
2019
The analog signals generated in the read-out electronics of particle detectors are shaped prior to the digitization in order to improve the signal to noise ratio (SNR). The real amplitude of the analog signal is then obtained using digital filters, which provides information about the energy deposited in the detector. The classical digital filters have a good performance in ideal situations with Gaussian electronic noise and no pulse shape distortion. However, high-energy particle colliders, such as the Large Hadron Collider (LHC) at CERN, can produce multiple simultaneous events, which produce signal pileup. The performance of classical digital filters deteriorates in these conditions sinc…
Accurate classification of childhood brain tumours by in vivo H-1 MRS - A multi-centre study
2013
Aims: To evaluate the accuracy of single-voxel Magnetic Resonance Spectroscopy (1H-MRS) as a non-invasive diagnostic aid for pediatric brain tumours in a multi-national study. Our hypotheses are (1) that automated classification based on 1H-MRS provides an accurate non-invasive diagnosis in multi-centre datasets and (2) using a protocol which increases the metabolite information improves the diagnostic accuracy. Methods: 78 patients under 16 years old with histologically proven brain tumours from 10 international centres were investigated. Discrimination of 29 medulloblastomas, 11 ependymomas and 38 pilocytic astrocytomas was evaluated. Single-voxel MRS was undertaken prior to diagnosis (1.…
SuperHistopath: A Deep Learning Pipeline for Mapping Tumor Heterogeneity on Low-Resolution Whole-Slide Digital Histopathology Images.
2021
High computational cost associated with digital pathology image analysis approaches is a challenge towards their translation in routine pathology clinic. Here, we propose a computationally efficient framework (SuperHistopath), designed to map global context features reflecting the rich tumor morphological heterogeneity. SuperHistopath efficiently combines i) a segmentation approach using the linear iterative clustering (SLIC) superpixels algorithm applied directly on the whole-slide images at low resolution (5x magnification) to adhere to region boundaries and form homogeneous spatial units at tissue-level, followed by ii) classification of superpixels using a convolution neural network (CN…
Comparison among different rainfall energy harvesting structures
2018
In this paper, an experimental comparison between different rainfall harvesting devices through the study of the electrical rectifying circuit is proposed. In more detail, three harvesting structures are considered: the cantilever, the bridge and the floating circle. Different waveforms were acquired and discussed. The processed data were compared in order to suggest the best choice for the rectifying circuit, from the simplest one to that most frequently endorsed in the technical literature.
Cartoon filter via adaptive abstraction
2016
We propose a non-parametric methodology to realize abstraction images.The redundant wavelet "a trous" algorithm is applied for details detection.An multi-scale circular median filter is used as a smoothing filter.The proposed algorithm is simple and fast on low-cost entry-level hardware. Abstraction in computer graphics defines a procedure that discriminates the essential information that is worth keeping. Usually details, that correspond to higher frequency components, allow to distinguish otherwise similar images. Vice versa, low frequencies are related to the main information, which are larger structures. Contours themselves may also be identified by high frequencies and separate each pi…
Rethinking the sGLOH Descriptor
2018
sGLOH (shifting GLOH) is a histogram-based keypoint descriptor that can be associated to multiple quantized rotations of the keypoint patch without any recomputation. This property can be exploited to define the best distance between two descriptor vectors, thus avoiding computing the dominant orientation. In addition, sGLOH can reject incongruous correspondences by adding a global constraint on the rotations either as an a priori knowledge or based on the data. This paper thoroughly reconsiders sGLOH and improves it in terms of robustness, speed and descriptor dimension. The revised sGLOH embeds more quantized rotations, thus yielding more correct matches. A novel fast matching scheme is a…