A review of deep learning techniques for speech processing
The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …
learning. The use of multiple processing layers has enabled the creation of models capable …
A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
Abstract Deep Transfer Learning (DTL) is a new paradigm of machine learning, which can
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …
A complete survey on generative ai (aigc): Is chatgpt from gpt-4 to gpt-5 all you need?
As ChatGPT goes viral, generative AI (AIGC, aka AI-generated content) has made headlines
everywhere because of its ability to analyze and create text, images, and beyond. With such …
everywhere because of its ability to analyze and create text, images, and beyond. With such …
[HTML][HTML] Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
Abstract Explainable Artificial Intelligence (XAI) is an emerging research topic of machine
learning aimed at unboxing how AI systems' black-box choices are made. This research field …
learning aimed at unboxing how AI systems' black-box choices are made. This research field …
A survey of deep active learning
Active learning (AL) attempts to maximize a model's performance gain while annotating the
fewest samples possible. Deep learning (DL) is greedy for data and requires a large amount …
fewest samples possible. Deep learning (DL) is greedy for data and requires a large amount …
[HTML][HTML] A comprehensive survey on machine learning-based big data analytics for IoT-enabled smart healthcare system
The outbreak of chronic diseases such as COVID-19 has made a renewed call for providing
urgent healthcare facilities to the citizens across the globe. The recent pandemic exposes …
urgent healthcare facilities to the citizens across the globe. The recent pandemic exposes …
Deep reinforcement learning in computer vision: a comprehensive survey
Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …
the powerful representation of deep neural networks. Recent works have demonstrated the …
Comparison of deep learning approaches to predict COVID-19 infection
TB Alakus, I Turkoglu - Chaos, Solitons & Fractals, 2020 - Elsevier
The SARS-CoV2 virus, which causes COVID-19 (coronavirus disease) has become a
pandemic and has expanded all over the world. Because of increasing number of cases day …
pandemic and has expanded all over the world. Because of increasing number of cases day …
Mel frequency cepstral coefficient and its applications: A review
ZK Abdul, AK Al-Talabani - IEEE Access, 2022 - ieeexplore.ieee.org
Feature extraction and representation has significant impact on the performance of any
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …
Deep autoencoder based energy method for the bending, vibration, and buckling analysis of Kirchhoff plates with transfer learning
In this paper, we present a deep autoencoder based energy method (DAEM) for the
bending, vibration and buckling analysis of Kirchhoff plates. The DAEM exploits the higher …
bending, vibration and buckling analysis of Kirchhoff plates. The DAEM exploits the higher …