[HTML][HTML] Deep learning-based models for environmental management: Recognizing construction, renovation, and demolition waste in-the-wild
The construction industry generates a substantial volume of solid waste, often destinated for
landfills, causing significant environmental pollution. Waste recycling is decisive in …
landfills, causing significant environmental pollution. Waste recycling is decisive in …
Developing high-dimensional machine learning models to improve generalization ability and overcome data insufficiency for mixed sugar fermentation simulation
Biorefinery can be promoted by building accurate machine learning models. This work
proposed a strategy to enhance model's generalization ability and overcome insufficient …
proposed a strategy to enhance model's generalization ability and overcome insufficient …
Efficient adaptive learning rate for convolutional neural network based on quadratic interpolation egret swarm optimization algorithm
Convolutional neural network (CNN) has recently become popular for addressing multi-
domain image classification. However, most existing methods frequently suffer from poor …
domain image classification. However, most existing methods frequently suffer from poor …
Layer-Wise Adaptive Gradient Norm Penalizing Method for Efficient and Accurate Deep Learning
S Lee - Proceedings of the 30th ACM SIGKDD Conference on …, 2024 - dl.acm.org
Sharpness-aware minimization (SAM) is known to improve the generalization performance
of neural networks. However, it is not widely used in real-world applications yet due to its …
of neural networks. However, it is not widely used in real-world applications yet due to its …
Online monitoring lignocellulosic particles by focus beam reflectance measurement for efficient bioprocessing
JW Yao, XY Huang, YH Lin, CG Liu, FW Bai - Bioresource Technology, 2024 - Elsevier
Lignocellulose presents a promising alternative to fossil fuels. Monitoring the mass and size
changes of lignocellulosic particles without disrupting the process can assist in adjusting …
changes of lignocellulosic particles without disrupting the process can assist in adjusting …
Identification of Soybean Planting Areas Combining Fused Gaofen-1 Image Data and U-Net Model
S Zhang, X Ban, T Xiao, L Huang, J Zhao, W Huang… - Agronomy, 2023 - mdpi.com
It is of great significance to accurately identify soybean planting areas for ensuring
agricultural and industrial production. High-resolution satellite remotely sensed imagery has …
agricultural and industrial production. High-resolution satellite remotely sensed imagery has …
Curvature in the Looking-Glass: Optimal Methods to Exploit Curvature of Expectation in the Loss Landscape
JA Duersch, TA Catanach, A Safonov… - arXiv preprint arXiv …, 2024 - arxiv.org
Harnessing the local topography of the loss landscape is a central challenge in advanced
optimization tasks. By accounting for the effect of potential parameter changes, we can alter …
optimization tasks. By accounting for the effect of potential parameter changes, we can alter …
A Hybrid Deep Learning Techniques Using BERT and CNN for Toxic Comments Classification
A Jessica, MS Sugiarto, S Achmad… - 2024 International …, 2024 - ieeexplore.ieee.org
Cyberbullying is a pervasive issue across all forms of media, affecting various demographics
and platforms indiscriminately. From social media networks to online forums and comment …
and platforms indiscriminately. From social media networks to online forums and comment …
Sensitivity Analysis of Gas Consumption in Gas Turbine Combined Cycle
Q Cao, S Chen, W Xiang - 2023 3rd International Conference …, 2023 - ieeexplore.ieee.org
In order to analyze the specific impact of key parameters of an internal combustion engine
on its economy, a gas consumption sensitivity analysis model based on a deep feed-forward …
on its economy, a gas consumption sensitivity analysis model based on a deep feed-forward …