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Now showing items 11-17 of 17
Learning graph affinities for spectral graph-based salient object detection
(
Elsevier Ltd
, 2017 , Article)
In this paper, we propose a novel method for learning graph affinities for salient object detection. First, we assume that a graph representation of an image is given with a predetermined connectivity rule and representative ...
Joint K-Means quantization for Approximate Nearest Neighbor Search
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
Recently, Approximate Nearest Neighbor (ANN) Search has become a very popular approach for similarity search on large-scale datasets. In this paper, we propose a novel vector quantization method for ANN, which introduces ...
Salient object segmentation based on linearly combined affinity graphs
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
In this paper, we propose a graph affinity learning method for a recently proposed graph-based salient object detection method, namely Extended Quantum Cuts (EQCut). We exploit the fact that the output of EQCut is ...
Generalized model of biological neural networks: Progressive operational perceptrons
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
Traditional Artificial Neural Networks (ANNs) such as Multi-Layer Perceptrons (MLPs) and Radial Basis Functions (RBFs) were designed to simulate biological neural networks
An optimized k-NN approach for classification on imbalanced datasets with missing data
(
Springer Verlag
, 2016 , Conference Paper)
In this paper, we describe our solution for the machine learning prediction challenge in IDA 2016. For the given problem of 2-class classification on an imbalanced dataset with missing data, we first develop an imputation ...
The effect of automated taxa identification errors on biological indices
(
Elsevier Ltd
, 2017 , Article)
In benthic macroinvertebrate biomonitoring systems, the target is to determine the status of ecosystems based on several biological indices. To increase cost-efficiency, computer-based taxa identification for image data ...
Convolutional Neural Networks for patient-specific ECG classification
(
IEEE
, 2015 , Conference Paper)
We propose a fast and accurate patient-specific electrocardiogram (ECG) classification and monitoring system using an adaptive implementation of 1D Convolutional Neural Networks (CNNs) that can fuse feature extraction and ...