… This study compares human-coded images posted during 2017's Hurricane Harvey to
machine-learned ‘deep learning’ classification methods. Our framework for feature extraction uses …

… deep learning has greater potential for shallow learning and may aid in solving small sample
problems, while traditional deep learning … are not small sample deep learning algorithms. …

… To address these challenges, this paper presents a deep learning approach to the OPF. The
learning model exploits the information available in the similar states of the system (which is …

… We present NeuroLKH, a novel algorithm that combines deep learning with the strong … (SGN)
with supervised learning for edge scores and unsupervised learning for node penalties, …

… This study includes an effective deep learning based framework for PQD classification. The
proposed framework has the ability to analyze in 1D and 2D domains in accordance with the …

… The main intent of this paper is to develop a novel robust model for detecting and preventing
HELLO flooding attacks using optimized deep learning approach. In this proposed research …

… Many deep learning approaches have recently been … presents an unsupervised deep
learning approach for intrusion … a unified objective function combining reconstruction error with …

… we study deep learning neural networks in combination with … As a general result, we find
that the combination of data quality and … From our investigations of learning curves and token …

… combines deep learning and robust optimization techniques. Unlike recent machine-learning …
iteratively added as necessary to the machine-learning model by a Column-and-Constraint-…

… Abstract—Deep learning (DL) has achieved remarkable progress over the past decade and
… t-way combination sparse coverage cannot take the coverage within each combination of …