… The field of deep learning in recommender system is … on deep learning-based recommender
systems. More concretely, we provide and devise a taxonomy of deep learning-based …

… In this paper, we introduce deep learning-based feature extraction for hyperspectral data …
is one of the deep architecture-based models, to learn deep features of hyperspectral data in …

… models have surpassed classical machine learning–based … review of more than 150 deep
learning–based models for text … performance of different deep learning models on popular …

… , Deep Learning (DL) has gained much attention in communication systems. In DL-based …
Motivated by this, in this letter, we present a DL-based framework for channel estimation in …

… deep learning-based vulnerability detection to relieve human experts from the tedious and
subjective task of manually defining features. Since deep learning … applying deep learning to …

… Such model-based methods utilize mathematical formulations that represent the underlying
… and the power of modern deep learning pipelines increases. Deep neural networks (DNNs) …

… learning, deep learning, statistics, EEG and signal processing with different meanings. For
example, in machine learning, '… Similarly, in deep learning, the term 'epoch' refers to one pass …

… Our deep learning-based approach demonstrates significant potential for learning schemes
which … We believe that a learning based approach holds enormous promise in tackling and …

… based transmissions. It allows learning of transmitter and receiver implementations as deep
… -defined radios and open-source deep learning software libraries. We extend the existing …

… This article surveys recent developments in deep learning based object detectors. Concise
overview of benchmark datasets and evaluation metrics used in detection is also provided …