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Smart Stethoscope
(IEEE, 2020)
In this study, a device named smart stethoscope that uses digital sensor technology for sound capture, active acoustics for noise cancellation and artificial intelligence (AI) for diagnosis of heart and lung diseases is ...
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets Using Deep Learning
(Springer, 2020)
Techniques used for spatio-temporal anomaly detection in an unsupervised settings has attracted great attention in recent years. It has extensive use in a wide variety of applications such as: medical diagnosis, sensor ...
Predatory Conversation Detection Using Transfer Learning Approach
(Springer International Publishing Ag, 2022)
Predatory conversation detection on social media can proactively prevent the netizens, including youngsters and children, from getting exploited by sexual predators. Earlier studies have majorly employed machine learning ...
MuscleNET: Smart Predictive Analysis for Muscular Activity Using Wearable Sensors
(Institute of Electrical and Electronics Engineers Inc., 2022)
Doing weightlifting training at home has become more popular during the pandemic. Unfortunately, exercising without professional help can lead to dangerous injuries such as muscle tearing. It is possible to create a smart ...
PREDICTING PATH LOSS DISTRIBUTIONS OF A WIRELESS COMMUNICATION SYSTEM FOR MULTIPLE BASE STATION ALTITUDES FROM SATELLITE IMAGES
(IEEE Computer Society, 2022)
It is expected that unmanned aerial vehicles (UAVs) will play a vital role in future communication systems. Optimum positioning of UAVs, serving as base stations, can be done through extensive field measurements or ray ...
Classification of ADHD using ensemble algorithms with deep learning and hand crafted features
(Institute of Electrical and Electronics Engineers Inc., 2019)
Attention Deficit Hyperactivity (ADHD) is a common neurodevelopmental disorder that typically appears in early childhood. Methods developed for diagnosing gives different results at different times. This is a major obstacle ...
The effect of data augmentation on ADHD diagnostic model using deep learning
(Institute of Electrical and Electronics Engineers Inc., 2019)
Attention Deficit Hyperactivity Disorder (ADHD) is a neuro-behavioral hyperactivity disorder. It is frequently seen in childhood and youth, and lasts a lifetime unless treated. The ADHD classification model should be ...
Multitype Learning via Multimodal Data Embedding
(Institute of Electrical and Electronics Engineers Inc., 2021)
This paper creates a multimodal retrieval system for image and text data in a multi-type learning approach that enables text-to-image, image-to-text, text-to-text, and image-to-image retrievals. As a practical solution, a ...
Benchmark Static API Call Datasets for Malware Family Classification
(Institute of Electrical and Electronics Engineers Inc., 2022)
Nowadays, malware and malware incidents are increasing daily, even with various antivirus systems and malware detection or classification methodologies. Machine learning techniques have been the main focus of the security ...
Multimodal retrieval with contrastive pretraining
(Institute of Electrical and Electronics Engineers Inc., 2021)
In this paper, we present multimodal data retrieval aided with contrastive pretraining. Our approach is to pretrain a contrastive network to assist in multimodal retrieval tasks. We work with multimodal data, which has ...