Now showing items 1-6 of 6
Deep receiver design for multi-carrier waveforms using CNNs
In this paper, a deep learning based receiver is proposed for a collection of multi-carrier wave-forms including both current and next-generation wireless communication systems. In particular, we propose to use a convolutional ...
A transfer-learning approach for accelerated MRI using deep neural networks
Purpose: Neural networks have received recent interest for reconstruction of undersampled MR acquisitions. Ideally, network performance should be optimized by drawing the training and testing data from the same domain. In ...
Multimodal analysis of personality traits on videos of self-presentation and induced behavior
Personality analysis is an important area of research in several fields, including psychology, psychiatry, and neuroscience. With the recent dramatic improvements in machine learning, it has also become a popular research ...
Deep learning for radar signal detection in electronic warfare systems
Detection of radar signals is the initial step for passive systems. Since these systems do not have prior information about received signal, application of matched filter and general likelihood ratio tests are infeasible. ...
AttentionBoost: learning what to attend for gland segmentation in histopathological images by boosting fully convolutional networks
Fully convolutional networks (FCNs) are widely used for instance segmentation. One important challenge is to sufficiently train these networks to yield good generalizations for hard-to-learn pixels, correct prediction of ...
Stance detection: a survey
(Association for Computing Machinery, 2020)
Automatic elicitation of semantic information from natural language texts is an important research problem with many practical application areas. Especially after the recent proliferation of online content through channels ...