Academic Articles & Research Papers

An optimized deep learning framework for temporally stable real-time face detection in unconstrained video streams

Abstract Face detection in real-time video streams remains challenging because of dynamic variations in illumination, pose, motion blur, and partial occlusion. This paper proposes an optimized deep learning framework that integrates YOLOv12...

Scalable and accurate deep learning with electronic health records

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variabl...

Deep Learning with R

Introduces deep learning systems using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples...

ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning

COVID-19 has become a global pandemic that has affected not only the health sector but also economic, social, and psychological well-being. Individuals are using social media platforms to communicate their feelings and sentiments about the ...

Applications of Shaped-Charge Learning

It is well known that deep learning (DNN) has strong limitations due to a lack of explainability and weak defense against possible adversarial attacks. These attacks would be a concern for autonomous teams producing a state of high entropy ...

Deep learning for environmental conservation

Deep Learning in Microscopy Image Analysis: A Survey

Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerg...

Analysis of Customer Churn Classification for Sinarmas Syariah Lhokseumawe Insurance Services Using Deep Learning Tabnet and Explainable AI

Customer churn is a major challenge in the insurance industry because it directly affects customer retention, business sustainability, and company profitability. Early identification of customers at risk of churn is therefore essential for ...

Comparison of Deep Learning Models for LAI Simulation and Interpretable Hydrothermal Coupling in the Loess Plateau

As the world’s largest loess deposit region, the Loess Plateau’s vegetation dynamics are crucial for its regional water–heat balance and ecosystem functioning. Leaf Area Index (LAI) serves as a key indicator bridging canopy architecture and...

Basics of Deep Learning: A Radiologist's Guide to Understanding Published Radiology Articles on Deep Learning

Artificial intelligence has been applied to many industries, including medicine. Among the various techniques in artificial intelligence, deep learning has attained the highest popularity in medical imaging in recent years. Many articles on...

A General Survey on Attention Mechanisms in Deep Learning

Attention is an important mechanism that can be employed for a variety of deep learning models across many different domains and tasks. This survey provides an overview of the most important attention mechanisms proposed in the literature. ...

"I Can't Fully Explain It, but Something Just Feels Off": A Qualitative Study of Danish Students' Bystander Perceptions of Sexual Violence Risk.

A comprehensive review on ensemble deep learning: Opportunities and challenges

In machine learning, two approaches outperform traditional algorithms: ensemble learning and deep learning. The former refers to methods that integrate multiple base models in the same framework to obtain a stronger model that outperforms t...

Deep learning in cancer diagnosis, prognosis and treatment selection

Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning acr...

Deep Learning in Medical Imaging

The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the low computing power and insufficient learn...

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...

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: 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...

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...

A Selective Overview of Deep Learning

Deep learning has achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a l...