Academic Articles & Research Papers

Deep Learning for Video Game Playing

In this paper, we review recent deep learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games. We analyze the unique requ...

Presenting the students’ academic achievement causal model based on goal orientation

Introduction: Several factors play a role in academic achievement, individual’s excellence and capability to do actions and tasks that the learner is in charge of in learning areas. The main goal of this study was to present academic ach...

A deep learning approach to predict blood-brain barrier permeability

The blood–brain barrier plays a crucial role in regulating the passage of 98% of the compounds that enter the central nervous system (CNS). Compounds with high permeability must be identified to enable the synthesis of brain medications for...

ACtriplet: An improved deep learning model for activity cliffs prediction by integrating triplet loss and pre-training

Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid m...

Image-based cotton leaf disease diagnosis using YOLO and faster R-CNN techniques

Abstract Cotton has, in recent years, become one of the most important cash crops worldwide while being impacted in yield from leaf disease which generally goes unnoticed in the early stage. Detection methods depend on manual efforts produc...

Jet-images — deep learning edition

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...

Deep learning for power quality

This paper aims to introduce deep learning to the power quality community by reviewing the latest applications and discussing the open challenges of this technology. Publications covering deep learning to power quality are stratified in ter...

Deep-learning-generated holography

We present a method for computer-generated holography based on deep learning. The inverse process of light propagation is regressed with a number of computationally generated speckle data sets. This method enables noniterative calculation o...

Jet-images — deep learning edition

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...

Deep learning for electroencephalogram (EEG) classification tasks: a review

OBJECTIVE: Electroencephalography (EEG) analysis has been an important tool in neuroscience with applications in neuroscience, neural engineering (e.g. Brain-computer interfaces, BCI's), and even commercial applications. Many of the analyti...

Deep learning approaches to biomedical image segmentation

The review covers automatic segmentation of images by means of deep learning approaches in the area of medical imaging. Current developments in machine learning, particularly related to deep learning, are proving instrumental in identificat...

Deep Learning and System Identification

Deep learning is a topic of considerable interest today. Since it deals with estimating - or learning - models, there are connections to the area of System Identification developed in the Automatic Control community. Such connections are ex...

Deep learning: a statistical viewpoint

The remarkable practical success of deep learning has revealed some major surprises from a theoretical perspective. In particular, simple gradient methods easily find near-optimal solutions to non-convex optimization problems, and despite g...

Image Segmentation Using Deep Learning: A Survey

Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, amon...

Deep Learning (CNN) and Transfer Learning: A Review

Abstract Deep Learning is a machine learning area that has recently been used in a variety of industries. Unsupervised, semi-supervised, and supervised-learning are only a few of the strategies that have been developed to accommodate differ...

Database Meets Deep Learning

Deep learning has recently become very popular on account of its incredible success in many complex datadriven applications, including image classification and speech recognition. The database community has worked on data-driven application...

Deep learning for financial applications : A survey

Deep Learning in Natural Language Processing

Deep Learning for Encrypted Traffic Classification: An Overview

Traffic classification has been studied for two decades and applied to a wide range of applications from QoS provisioning and billing in ISPs to security-related applications in firewalls and intrusion detection systems. Port-based, data pa...

Assessment of hydrogen vehicle fuel economy using MRAC based on deep learning

Abstract Many controllers have been developed to control the motors of electric vehicles, but in the case of hydrogen vehicles, more delicate control is required, because power is provided through hybridization with batteries. The use of de...