|
|
|
|
|
Fahim Sufi
GPT (Generative Pre-trained Transformer) represents advanced language models that have significantly reshaped the academic writing landscape. These sophisticated language models offer invaluable support throughout all phases of research work, facilitatin...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sara Rajaram and Cassie S. Mitchell
The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) into different modalities and data types is essential to improve Deep Learning (DL) for predictive medicine. This work presents DACMVA, a novel framework ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yingcong Huang, Kunal Chaturvedi, Al-Akhir Nayan, Mohammad Hesam Hesamian, Ali Braytee and Mukesh Prasad
Parkinson?s disease (PD) is a chronic brain disorder affecting millions worldwide. It occurs when brain cells that produce dopamine, a chemical controlling movement, die or become damaged. This leads to PD, which causes problems with movement, balance, a...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wenhao Sun, Yidong Zou, Yunhe Wang, Boyi Xiao, Haichuan Zhang and Zhihuai Xiao
In the practical production environment, the complexity and variability of hydroelectric units often result in a need for more fault data, leading to inadequate accuracy in fault identification for data-driven intelligent diagnostic models. To address th...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lijun Zu, Wenyu Qi, Hongyi Li, Xiaohua Men, Zhihui Lu, Jiawei Ye and Liang Zhang
The digital transformation of banks has led to a paradigm shift, promoting the open sharing of data and services with third-party providers through APIs, SDKs, and other technological means. While data sharing brings personalized, convenient, and enriche...
ver más
|
|
|
|
|
|
|
|
|
|
|
Min Ma, Shanrong Liu, Shufei Wang and Shengnan Shi
Automatic modulation classification (AMC) plays a crucial role in wireless communication by identifying the modulation scheme of received signals, bridging signal reception and demodulation. Its main challenge lies in performing accurate signal processin...
ver más
|
|
|
|
|
|
|
|
|
|
|
Fengyun Xie, Gang Li, Hui Liu, Enguang Sun and Yang Wang
In the context of addressing the challenge posed by limited fault samples in agricultural machinery rolling bearings, especially when early fault characteristics are subtle, this study introduces a novel approach. The proposed multi-domain fault diagnosi...
ver más
|
|
|
|
|
|
|
|
|
|
|
François Legrand, Richard Macwan, Alain Lalande, Lisa Métairie and Thomas Decourselle
Automated Cardiac Magnetic Resonance segmentation serves as a crucial tool for the evaluation of cardiac function, facilitating faster clinical assessments that prove advantageous for both practitioners and patients alike. Recent studies have predominant...
ver más
|
|
|
|
|
|
|
|
|
|
|
Fabi Prezja, Leevi Annala, Sampsa Kiiskinen and Timo Ojala
Diagnosing knee joint osteoarthritis (KOA), a major cause of disability worldwide, is challenging due to subtle radiographic indicators and the varied progression of the disease. Using deep learning for KOA diagnosis requires broad, comprehensive dataset...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mohammad Alhumaid and Ayman G. Fayoumi
Paranasal sinus pathologies, particularly those affecting the maxillary sinuses, pose significant challenges in diagnosis and treatment due to the complex anatomical structures and diverse disease manifestations. The aim of this study is to investigate t...
ver más
|
|
|
|
|
|