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Deep learning applications in games: a survey from a data perspective
This paper presents a comprehensive review of deep learning applications in the video game industry, focusing on how these techniques can be utilized...
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A review of deep learning and Generative Adversarial Networks applications in medical image analysis
Nowadays, computer-aided decision support systems (CADs) for the analysis of images have been a perennial technique in the medical imaging field. In...
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Deep learning implementations in mining applications: a compact critical review
Deep learning is a sub-field of artificial intelligence that combines feature engineering and classification in one method. It is a data-driven...
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Demystifying API misuses in deep learning applications
Deep Learning (DL) is achieving staggering performance on an increasing number of applications in various areas. Meanwhile, its associated...
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Common challenges of deep reinforcement learning applications development: an empirical study
Machine Learning (ML) is increasingly being adopted in different industries. Deep Reinforcement Learning (DRL) is a subdomain of ML used to produce...
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Privacy-preserving deep learning in medical informatics: applications, challenges, and solutions
Deep Learning (DL) has already shown tremendous potential in designing intelligent clinical support systems in biomedicine. Data privacy plays a...
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Deep learning implementation of image segmentation in agricultural applications: a comprehensive review
Image segmentation is a crucial task in computer vision, which divides a digital image into multiple segments and objects. In agriculture, image...
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English–Vietnamese Machine Translation Using Deep Learning for Chatbot Applications
Recently, artificial intelligence-based machine translation has been much improved over traditional methods. A machine translator is very useful for...
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A review of deep learning techniques in audio event recognition (AER) applications
In our day-to-day life, observation of human and social actions are highly important for public protection and security. Additionally, identifying...
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A meta-analysis on diabetic retinopathy and deep learning applications
Diabetic retinopathy is one of the negative effects of diabetes on the eye. Early diagnosis of this disease, which can progress to blindness, is very...
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Triplet attention-based deep learning model for hierarchical image classification of household items for robotic applications
Hierarchical classification is important in automation and robotics in terms of providing extra pieces of information about the classified object. In...
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Deep learning in multimedia healthcare applications: a review
The increase in chronic diseases has affected the countries’ health system and economy. With the recent COVID-19 virus, humanity has experienced a...
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Deep reinforcement learning for multi-class imbalanced training: applications in healthcare
With the rapid growth of memory and computing power, datasets are becoming increasingly complex and imbalanced. This is especially severe in the...
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The deep learning applications in IoT-based bio- and medical informatics: a systematic literature review
Nowadays, machine learning (ML) has attained a high level of achievement in many contexts. Considering the significance of ML in medical and...
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A survey on spatio-temporal series prediction with deep learning: taxonomy, applications, and future directions
With the rapid development of data acquisition and storage technology, spatio-temporal (ST) data in various fields are growing explosively, so many...
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Deep learning based diabetic retinopathy screening for resource constraint applications
Diabetic Retinopathy (DR) poses a critical health concern, affecting millions of individuals globally, particularly in light of the increasing...
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Deep learning applications for lung cancer diagnosis: A systematic review
Lung cancer has been one of the most prevalent disease in recent years. According to the research of this field, more than 200,000 cases are...
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Applications of Deep Learning in Satellite Communication: A Survey
Satellite communication is a key aspect of future 6G networks, and the impact of artificial intelligence technology utilizing deep learning on...
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Applications of Game Theory in Deep Learning
This book aims to unravel the complex tapestry that interweaves strategic decision-making models with the forefront of deep learning techniques. Applic...
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Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems
Modern machine learning (ML) systems commonly use stochastic gradient descent (SGD) to train ML models. However, SGD relies on random data order to...
