A Survey on Hyperparameters Optimization of Deep Learning for Time Series Classification
AH Fristiana, SAI Alfarozi, AE Permanasari… - IEEE …, 2024 - ieeexplore.ieee.org
Time series classification (TSC) is essential in various application domains for
understanding system dynamics. The adoption of deep learning has advanced TSC, but …
understanding system dynamics. The adoption of deep learning has advanced TSC, but …
Human activity recognition in maintenance centers to reduce wasted time
This paper proposed a system that extracts workers' poses from live cam and video clips
using mode classification. In this paper, we tested two algorithms to detect worker activity …
using mode classification. In this paper, we tested two algorithms to detect worker activity …
[PDF][PDF] Enhancing Health Monitoring using Efficient Hyperparameter Optimization
R Singhal - Journal of Artificial Intelligence, 2022 - researchgate.net
Nowadays, healthcare problems among elders have been increasing at an unprecedented
rate, and every year, more than a quarter of the elderly people face weakening injuries such …
rate, and every year, more than a quarter of the elderly people face weakening injuries such …
Human Activity Recognition in Car Workshop
M Omar, A Atia - … Journal of Advanced Computer Science and …, 2022 - search.proquest.com
Human activity recognition has become so widespread in recent times. Due to the modern
advancements of technology, it has become an important solution to many prob-lems in …
advancements of technology, it has become an important solution to many prob-lems in …
Data Driven Casing Collar Feature Detection and Identification for Automated Depth Estimation for Wireline
SK Raman, M Abuhaikal - Fourth EAGE Digitalization Conference & …, 2024 - earthdoc.org
Accurately estimating tool-string depth is extremely crucial for wireline operations. Tool-
string depth estimation primary based on tracking cable length is challenging and inaccurate …
string depth estimation primary based on tracking cable length is challenging and inaccurate …