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Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection
This work combines these two approaches in a convolutional recurrent neural network (CRNN) and applies it on a polyphonic sound event detection task and observes a considerable improvement for four different datasets consisting of everyday sound events. Expand
Recurrent neural networks for polyphonic sound event detection in real life recordings
In this paper we present an approach to polyphonic sound event detection in real life recordings based on bi-directional long short term memory (BLSTM) recurrent neural networks (RNNs). A singleExpand
Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects
The results presented in this study demonstrate the potential of the suggested approach for early AD diagnosis and an important role of MRI in the MCI-to-AD conversion prediction. Expand
Robust detection of periodic time series measured from biological systems
This work proposes a general-purpose robust testing procedure for finding periodic sequences in multiple time series data based on a robust spectral estimator which is incorporated into the hypothesis testing framework using a so-called g-statistic together with correction for multiple testing. Expand
Computational Framework for Simulating Fluorescence Microscope Images With Cell Populations
A simulation platform for generating synthetic images of fluorescence-stained cell populations with realistic properties that enable the validation of analysis methods for automated image cytometry and comparison of their performance is presented. Expand
Polyphonic sound event detection using multi label deep neural networks
Frame-wise spectral-domain features are used as inputs to train a deep neural network for multi label classification in this work and the proposed method improves the accuracy by 19% percentage points overall. Expand
Recognition of acoustic events using deep neural networks
For an acoustic event classification task containing 61 distinct classes, classification accuracy of the neural network classifier excels that of the conventional Gaussian mixture model based hidden Markov model classifier. Expand
Car type recognition with Deep Neural Networks
Two data driven frameworks are considered: a deep neural network and a support vector machine using SIFT features for automatic recognition of cars of four types: Bus, Truck, Van and Small car. Expand
Benchmark set of synthetic images for validating cell image analysis algorithms
This article presents a synthetic image set for validation of cell image analysis algorithms, and proposes to use the simulated images for benchmarking along with manually labeled images, and presents case studies of tuning and testing a cell imageAnalysis algorithm based on simulated images. Expand
Clustering benefits in mobile-centric WiFi positioning in multi-floor buildings
A comparative analysis between different clustering methods, together with a novel metric, called the Penalized Logarithmic Gaussian Distance metric which can boost the performance of the clustering. Expand