How important are activation functions in regression and classification? A survey, performance comparison, and future directions
AD Jagtap, GE Karniadakis - Journal of Machine Learning for …, 2023 - dl.begellhouse.com
Inspired by biological neurons, the activation functions play an essential part in the learning
process of any artificial neural network (ANN) commonly used in many real-world problems …
process of any artificial neural network (ANN) commonly used in many real-world problems …
Time series classification using diversified ensemble deep random vector functional link and resnet features
WX Cheng, PN Suganthan, R Katuwal - Applied Soft Computing, 2021 - Elsevier
Abstract Random Vector Functional Link (RVFL) is popular among researchers in many
areas of machine learning. RVFL is preferred by many researchers as RVFL can produce …
areas of machine learning. RVFL is preferred by many researchers as RVFL can produce …
Real-time emotion classification using eeg data stream in e-learning contexts
In face-to-face and online learning, emotions and emotional intelligence have an influence
and play an essential role. Learners' emotions are crucial for e-learning system because …
and play an essential role. Learners' emotions are crucial for e-learning system because …
A Docker-based federated learning framework design and deployment for multi-modal data stream classification
In the high-performance computing (HPC) domain, federated learning has gained immense
popularity. Especially in emotional and physical health analytics and experimental facilities …
popularity. Especially in emotional and physical health analytics and experimental facilities …
TSTFNN: Performance Enhancement for Fuzzy Neural Network in Performance Monitoring of Industrial Flotation Processes
Numerous studies on learning algorithms have been done in the neural networks
community, however concerning to training strategy is limited. In this article, to enhance the …
community, however concerning to training strategy is limited. In this article, to enhance the …
Neural networks with à la carte selection of activation functions
M Sipper - SN Computer Science, 2021 - Springer
Activation functions (AFs), which are pivotal to the success (or failure) of a neural network,
have received increased attention in recent years, with researchers seeking to design novel …
have received increased attention in recent years, with researchers seeking to design novel …
An Ensemble Framework for Glaucoma Classification Using Fundus Images
Glaucoma is an irreversible progressive vision condition that can lead to permanent
sightlessness. With null early-stage symptoms, it is critical to prevent in advanced stages of …
sightlessness. With null early-stage symptoms, it is critical to prevent in advanced stages of …
The Influence of Non-learnable Activation Functions on the Positioning Performance of Deep Learning-Based Fingerprinting Models Trained with Small CSI Sample …
AS Lutakamale, YZ Manyesela - … of the Indian National Academy of …, 2022 - Springer
Activation functions, being mathematical 'gates' in between the input feeding the current
neuron and its output going to the next layer, is very crucial in the training of deep learning …
neuron and its output going to the next layer, is very crucial in the training of deep learning …
An Ensemble Neural Model for Classification of LADA Diabetes Case, Control and Variable Importance
LADA Diabetes is a complex disease, but often dismissed as a potential individual disease
within its own right. A comprehensive understanding of previously unknown aspects of …
within its own right. A comprehensive understanding of previously unknown aspects of …
[HTML][HTML] 基于卡尔曼滤波器和多层感知器的大麦幼苗最优生长参数预测
黄云龙， 李正权， 孙煜嘉 - 物联网学报 - infocomm-journal.com
摘要为了提高生长舱大麦幼苗的质量和种植效率, 首先利用卡尔曼滤波算法对传感器采集的数据
进行处理, 有效降低了环境因素和传感器本身误差的影响, 提高了采集数据的精度 …
进行处理, 有效降低了环境因素和传感器本身误差的影响, 提高了采集数据的精度 …