Search Results for author:
Found 18 papers, 1 papers with code
Evolution of MAC Protocols in the Machine Learning Decade: A Comprehensive Survey
Furthermore, we provide an overview of the ML techniques that have been considered in this context.
Non-Negative Matrix Factorization with Scale Data Structure Preservation
The model described in this paper belongs to the family of non-negative matrix factorization methods designed for data representation and dimension reduction.
Leveraging Centric Data Federated Learning Using Blockchain For Integrity Assurance
Machine learning abilities have become a vital component for various solutions across industries, applications, and sectors.
A Learning Framework for Bandwidth-Efficient Distributed Inference in Wireless IoT
To this end, we propose a novel deep learning-based framework for compressing and quantizing the observations of correlated sensors.
Energy Disaggregation using Variational Autoencoders
In this paper we address these issues and propose an energy disaggregation approach based on the variational autoencoders framework.
PRVNet: A Novel Partially-Regularized Variational Autoencoders for Massive MIMO CSI Feedback
In a multiple-input multiple-output frequency-division duplexing (MIMO-FDD) system, the user equipment (UE) sends the downlink channel state information (CSI) to the base station to report link status.
BLCS: Brain-Like based Distributed Control Security in Cyber Physical Systems
To deal with this issue, we propose a brain-like based distributed control security (BLCS) architecture for F-RON in CPS, by introducing a brain-like security (BLS) scheme.
Efficient No-Reference Quality Assessment and Classification Model for Contrast Distorted Images
In this paper, an efficient Minkowski Distance based Metric (MDM) for no-reference (NR) quality assessment of contrast distorted images is proposed.
FSITM: A Feature Similarity Index For Tone-Mapped Images
In this work, based on the local phase information of images, an objective index, called the feature similarity index for tone-mapped images (FSITM), is proposed.
MUG: A Parameterless No-Reference JPEG Quality Evaluator Robust to Block Size and Misalignment
The proposed metric called median of unique gradients (MUG) is based on the very simple facts of unique gradient magnitudes of JPEG compressed images.
Mean Deviation Similarity Index: Efficient and Reliable Full-Reference Image Quality Evaluator
Motivated by a recent work that utilizes the standard deviation pooling, a general formulation of the DP is presented in this paper and used to compute a final score from the proposed GS and CS maps.
Ranked #4 on
Image Quality Assessment
on MSU FR VQA Database
Modified Hausdorff Fractal Dimension (MHFD)
The Hausdorff fractal dimension has been a fast-to-calculate method to estimate complexity of fractal shapes.
Deviation Based Pooling Strategies For Full Reference Image Quality Assessment
In this paper, we propose to use the mean absolute deviation (MAD) and show that it is a more robust and accurate pooling strategy for a wider range of IQAs.
A Multiple-Expert Binarization Framework for Multispectral Images
In this work, a multiple-expert binarization framework for multispectral images is proposed.
A maximal-information color to gray conversion method for document images: Toward an optimal grayscale representation for document image binarization
A novel method to convert color/multi-spectral images to gray-level images is introduced to increase the performance of document binarization methods.
Large Margin Low Rank Tensor Analysis
Furthermore, the generalization of our model based on similarity between the learned low dimensional embeddings can be viewed as counterpart of recognition of human brain.
Unsupervised ensemble of experts (EoE) framework for automatic binarization of document images
After building the endorsement graph of the ensemble for an input document image based on the confidentness of the experts, the saturated opinions are consolidated, and then the schools of experts are identified by thresholding the consolidated endorsement graph.
