On the public citation graph
Smish: A Novel Activation Function for Deep Learning Methods
0 signed · 127 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-7908-2604-3_16openalex-snapshot
Large-Scale Machine Learning with Stochastic Gradient Descent
inferredcites →https://doi.org/10.1007/s11760-020-01746-9openalex-snapshot
Parametric rectified nonlinear unit (PRenu) for convolution neural networks
inferredcites →https://doi.org/10.1007/s13370-020-00850-wopenalex-snapshot
Some special families of holomorphic and Al-Oboudi type bi-univalent functions related to k-Fibonacci numbers involving modified Sigmoid activation function
inferredcites →https://doi.org/10.1016/j.eswa.2020.114048openalex-snapshot
Ensemble of convolutional neural networks trained with different activation functions
inferredcites →https://doi.org/10.1016/j.eswa.2021.115892openalex-snapshot
Quantum ReLU activation for Convolutional Neural Networks to improve diagnosis of Parkinson’s disease and COVID-19
inferredcites →https://doi.org/10.1016/j.jco.2022.101646openalex-snapshot
A proof of convergence for gradient descent in the training of artificial neural networks for constant target functions
inferredcites →https://doi.org/10.1016/j.neucom.2020.11.068openalex-snapshot
PFLU and FPFLU: Two novel non-monotonic activation functions in convolutional neural networks
inferredcites →https://doi.org/10.1016/j.neucom.2021.02.030openalex-snapshot
Efficient activation functions for embedded inference engines
inferredcites →https://doi.org/10.1016/j.neucom.2021.06.067openalex-snapshot
Logish: A new nonlinear nonmonotonic activation function for convolutional neural network
inferredcites →https://doi.org/10.1016/j.neunet.2021.01.026openalex-snapshot
A survey on modern trainable activation functions
inferredcites →https://doi.org/10.1016/j.neunet.2022.01.001openalex-snapshot
Discovering Parametric Activation Functions
inferredcites →https://doi.org/10.1063/1.5090752openalex-snapshot
Prediction of vehicle casualties in major traffic accidents based on neural network
inferredcites →https://doi.org/10.1080/23273798.2021.1927120openalex-snapshot
Learning fast while avoiding spurious excitement and overcoming cue competition requires setting unachievable goals: reasons for using the logistic activation function in learning to predict categorical outcomes
inferredcites →https://doi.org/10.1088/1612-202x/abd23copenalex-snapshot
A novel quantum neural network based on multi-level activation function
inferredcites →https://doi.org/10.1088/1742-6596/1889/2/022007openalex-snapshot
Exploring the possibility of applying different neuronal activation functions to a single-circuit ACS
inferredcites →https://doi.org/10.1109/access.2020.3017436openalex-snapshot
Effective Activation Functions for Homomorphic Evaluation of Deep Neural Networks
inferredcites →https://doi.org/10.1109/csci.2016.0225openalex-snapshot
CIFAR-10: KNN-Based Ensemble of Classifiers
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00090openalex-snapshot
Adversarial Examples Improve Image Recognition
inferredcites →https://doi.org/10.1109/ijcnn.2019.8852023openalex-snapshot
The Cramming, Softening and Integrating Learning Algorithm with Parametric ReLU Activation Function for Binary Input/Output Problems
inferredcites →https://doi.org/10.1109/tcsii.2021.3082941openalex-snapshot
Efficient Hardware Implementation of DNN-Based Speech Enhancement Algorithm With Precise Sigmoid Activation Function
inferredcites →https://doi.org/10.1109/tie.2021.3139202openalex-snapshot
Multiple Activation Functions and Data Augmentation-Based Lightweight Network for In Situ Tool Condition Monitoring
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3394486.3403203openalex-snapshot
Measuring Model Complexity of Neural Networks with Curve Activation Functions
inferredcites →https://doi.org/10.2174/2213275911666181025143029openalex-snapshot
Analysis of Non-Linear Activation Functions for Classification Tasks Using Convolutional Neural Networks
inferredcites →https://doi.org/10.3390/s21030728openalex-snapshot
Multi-Block Color-Binarized Statistical Images for Single-Sample Face Recognition
inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-snapshot
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
inferredcites →https://doi.org/10.48550/arxiv.1902.06853openalex-snapshot
On the Impact of the Activation Function on Deep Neural Networks Training
inferredcites →https://doi.org/10.48550/arxiv.1905.11946openalex-snapshot
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
inferredcites →https://doi.org/10.52866/ijcsm.2022.01.01.005openalex-snapshot
Detecting The Speaker Language Using CNN Deep Learning Algorithm
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-47640-2_18openalex-snapshot
PumaMedNet-CXR: An Explainable Generative Artificial Intelligence for the Analysis and Classification of Chest X-Ray Images
inferred← citeshttps://doi.org/10.1007/978-3-032-18334-7_4openalex-snapshot
An Efficient Approach to Identify Fake News Using Machine Learning Algorithms
inferred← citeshttps://doi.org/10.1007/978-981-92-0229-4_4openalex-snapshot
Resu: A Regularized and Non-monotonic Activation Function for Convolution Neural Network
inferred← citeshttps://doi.org/10.1007/978-981-95-0441-1_6openalex-snapshot
Short Term Load Forecasting for Effective Trading in Energy Market Using Artificial Neural Networks and ADAM Optimizer
inferred← citeshttps://doi.org/10.1007/s00500-023-09279-2openalex-snapshot
αSechSig and αTanhSig: two novel non-monotonic activation functions
inferred← citeshttps://doi.org/10.1007/s00521-023-09035-5openalex-snapshot
Gish: a novel activation function for image classification
inferred← citeshttps://doi.org/10.1007/s00521-024-10935-3openalex-snapshot
Constructing a smoothed Leaky ReLU using a linear combination of the smoothed ReLU and identity function
inferred← citeshttps://doi.org/10.1007/s00521-025-11704-6openalex-snapshot
S2LU: An Activation Function Based on Skew Student's t-distribution for Improved Neural Network Performance
inferred← citeshttps://doi.org/10.1007/s00521-025-11759-5openalex-snapshot
A multi-objective whale optimization for solving combinatorial optimization problems via Hopfield neural networks
inferred← citeshttps://doi.org/10.1007/s10044-024-01277-wopenalex-snapshot
ErfReLU: adaptive activation function for deep neural network
inferred← citeshttps://doi.org/10.1007/s10044-024-01327-3openalex-snapshot
ShuffleNeMt: modern lightweight convolutional neural network architecture
inferred← citeshttps://doi.org/10.1007/s11227-024-06057-1openalex-snapshot
Trish: an efficient activation function for CNN models and analysis of its effectiveness with optimizers in diagnosing glaucoma
inferred← citeshttps://doi.org/10.1007/s11227-025-07164-3openalex-snapshot
Generating a large family of nonlinear activation functions (LFNAFs) in neural networks
inferred← citeshttps://doi.org/10.1007/s13042-025-02678-xopenalex-snapshot
Method of predicting the pseudo alumina concentration during aluminum electrolysis based on a Mexh-LSTM network
inferred← citeshttps://doi.org/10.1007/s13278-024-01294-xopenalex-snapshot
Hybrid annotation and classification for predicting attitudes towards COVID-19 vaccines for Arabic tweets
inferred← citeshttps://doi.org/10.1007/s40860-024-00221-3openalex-snapshot
Trainable Gaussian-based activation functions for sensor-based human activity recognition
inferred← citeshttps://doi.org/10.1007/s44163-026-01379-wopenalex-snapshot
Adaptive knowledge graph and learning path generation algorithm for artificial intelligence
inferred← citeshttps://doi.org/10.1016/b978-0-443-29306-1.00002-8openalex-snapshot
Improving deep learning models
inferred← citeshttps://doi.org/10.1016/j.asoc.2025.114291openalex-snapshot
Enhanced Generative Adversarial Network with Leaked Information (E-LeakGAN): A deep learning framework for synthesizing computational creativity in scientific domain
inferred← citeshttps://doi.org/10.1016/j.asoc.2026.116386openalex-snapshot
Design of zero-centered monotonic unsaturated odd activation functions for deep neural networks in image recognition
inferred← citeshttps://doi.org/10.1016/j.dsp.2025.105579openalex-snapshot
AdLU: Adaptive double parametric activation functions
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.122102openalex-snapshot
Novel deep learning models with novel integrated activation functions for autism screening: AutiNet and MinAutiNet
inferred← citeshttps://doi.org/10.1016/j.eswa.2026.131953openalex-snapshot
MishReLU: A hybrid activation function for deep neural networks
inferred← citeshttps://doi.org/10.1016/j.heliyon.2022.e11382openalex-snapshot
Predicting factors affecting the intention to use a 3PL during the COVID-19 pandemic: A machine learning ensemble approach
inferred← citeshttps://doi.org/10.1016/j.jece.2026.121275openalex-snapshot
An intelligent sensing platform integrating smartphone-based ratiometric fluorescence probe and feed-forward neural network (FFNN) for pH detection in aqueous samples
inferred← citeshttps://doi.org/10.1016/j.jpubtr.2023.100076openalex-snapshot
Utilizing a machine learning ensemble to evaluate the service quality and passenger satisfaction among public transportations
inferred← citeshttps://doi.org/10.1016/j.jwpe.2026.109542openalex-snapshot
Modeling haloketones in drinking water using conformable neural networks: a case study of Jinhua, China
inferred← citeshttps://doi.org/10.1016/j.knosys.2024.112502openalex-snapshot
Activation function optimization scheme for image classification
inferred← citeshttps://doi.org/10.1016/j.patcog.2025.111737openalex-snapshot
Rethinking iterative stereo matching from a diffusion bridge model perspective
inferred← citeshttps://doi.org/10.1016/j.rsase.2025.101706openalex-snapshot
The use of Unmanned Aerial Vehicle (UAV) remotely sensed data and biophysical variables to predict maize Above-Ground Biomass (AGB) in small-scale farming systems
inferred← citeshttps://doi.org/10.1016/j.sigpro.2026.110623openalex-snapshot
Smish least mean fourth based spline adaptive algorithm for nonlinear adaptive feedback control in hearing aids
inferred← citeshttps://doi.org/10.1016/j.tifs.2024.104821openalex-snapshot
Deep learning-assisted fluorescence spectroscopy for food quality and safety analysis
inferred← citeshttps://doi.org/10.1016/j.triboint.2023.109184openalex-snapshot
Prediction of friction coefficient of polymer surface using variational mode decomposition and machine learning algorithm based on noise features
inferred← citeshttps://doi.org/10.1038/s41598-025-17671-1openalex-snapshot
Hybrid CNN-BLSTM architecture for classification and detection of arrhythmia in ECG signals
inferred← citeshttps://doi.org/10.1063/5.0223811openalex-snapshot
Analyzing performance of activation functions in logic satisfiability hopfield neural network
inferred← citeshttps://doi.org/10.1063/5.0312806openalex-snapshot
Hybrid optimization approaches for optimal and diverse solutions in discrete hopfield neural network
inferred← citeshttps://doi.org/10.1080/03772063.2023.2173667openalex-snapshot
Big Data Classification Using Enhanced Dynamic KPCA and Convolutional Multi-Layer Bi-LSTM Network
inferred← citeshttps://doi.org/10.1080/10095020.2026.2673300openalex-snapshot
Forest carbon stock estimation in Wuyishan National Park using multisource data and Bayesian-optimized residual dropout network
inferred← citeshttps://doi.org/10.1080/17455030.2023.2239368openalex-snapshot
Machine intelligence aware electricity theft detection for smart metering applications
inferred← citeshttps://doi.org/10.1088/1361-6501/ae06c1openalex-snapshot
Dilated convolution and edge fusion network for crack edge detection
inferred← citeshttps://doi.org/10.1088/2632-2153/ac9fa5openalex-snapshot
Coot optimization based Enhanced Global Pyramid Network for 3D hand pose estimation
inferred← citeshttps://doi.org/10.1109/access.2022.3218322openalex-snapshot
Clothes Retrieval Using M-AlexNet With Mish Function and Feature Selection Using Joint Shannon’s Entropy Pearson’s Correlation Coefficient
inferred← citeshttps://doi.org/10.1109/access.2023.3276298openalex-snapshot
HcLSH: A Novel Non-Linear Monotonic Activation Function for Deep Learning Methods
inferred← citeshttps://doi.org/10.1109/access.2023.3315308openalex-snapshot
PolyLU: A Simple and Robust Polynomial-Based Linear Unit Activation Function for Deep Learning
inferred← citeshttps://doi.org/10.1109/access.2025.3574398openalex-snapshot
P-GELU: A Novel Activation Function to Optimize Whisper for Darija Speech Translation
inferred← citeshttps://doi.org/10.1109/access.2025.3581065openalex-snapshot
Assessment of Scientific Creative-Potential by Near-Infrared Spectroscopy Using Brain-Network-Based Deep-Fuzzy Classifier
inferred← citeshttps://doi.org/10.1109/access.2026.3653891openalex-snapshot
ExpAbsTanH: A Novel Activation Function for Image and Video-Based Human Activity Recognition
inferred← citeshttps://doi.org/10.1109/bibm66473.2025.11356390openalex-snapshot
An Efficient Hierarchical Network for Segmentation of Linear Structures in Biomedical Images
inferred← citeshttps://doi.org/10.1109/ic2pct60090.2024.10486545openalex-snapshot
Prediction of Alzheimer’S Disease from Magnetic Resonance Images (MRI)
inferred← citeshttps://doi.org/10.1109/icassp49660.2025.10889955openalex-snapshot
HANet: A Harmonic Attention-Based Network for Singing Melody Extraction from Polyphonic Music
inferred← citeshttps://doi.org/10.1109/iccit57492.2022.10056025openalex-snapshot
An Efficient Deep Learning Approach for Brain Tumor Segmentation using 3D Convolutional Neural Network
inferred← citeshttps://doi.org/10.1109/iccvw60793.2023.00147openalex-snapshot
Tiny and Efficient Model for the Edge Detection Generalization
inferred← citeshttps://doi.org/10.1109/icsip61881.2024.10671481openalex-snapshot
Efficient Stage Features for Edge Detection
inferred← citeshttps://doi.org/10.1109/lawp.2024.3391311openalex-snapshot
Sensing Matrix Prediction From Back-Scattered Data in Computational Microwave Imaging
inferred← citeshttps://doi.org/10.1109/prai59366.2023.10331944openalex-snapshot
CsiTransformer: A Limited-sample 6G Channel State Information Feedback Model
inferred← citeshttps://doi.org/10.1109/prai59366.2023.10332010openalex-snapshot
Charging Time Prediction of Electric Vehicle Charging Pile via Momentum-incorporated Non-negative Latent-factorization-of-tensors with Swish-regularization
inferred← citeshttps://doi.org/10.1109/speedam61530.2024.10609167openalex-snapshot
Addressing Integration Challenges in Vehicle Roll and Pitch Estimation Using Neural Networks
inferred← citeshttps://doi.org/10.1109/tgrs.2026.3664446openalex-snapshot
CODI: Contextual Object Detection via Image Inpainting
inferred← citeshttps://doi.org/10.1117/1.jei.34.2.023001openalex-snapshot
Edge detector based on multi-scale feature fusion: a robust convolutional neural network–based edge detector
inferred← citeshttps://doi.org/10.1155/cplx/8233876openalex-snapshot
AHerfReLU: A Novel Adaptive Activation Function Enhancing Deep Neural Network Performance
inferred← citeshttps://doi.org/10.1177/1088467x251337929openalex-snapshot
HDAF: A novel activation function for image classification
inferred← citeshttps://doi.org/10.1177/18758967251343172openalex-snapshot
Balanced Learnable Activation Function (BLAF): Enhancing Classification Accuracy in Deep Neural Networks
inferred← citeshttps://doi.org/10.1371/journal.pone.0304469openalex-snapshot
A Hybrid convolution neural network for the classification of tree species using hyperspectral imagery
inferred← citeshttps://doi.org/10.1371/journal.pone.0315127openalex-snapshot
geodl: An R package for geospatial deep learning semantic segmentation using torch and terra
inferred← citeshttps://doi.org/10.1371/journal.pone.0317181openalex-snapshot
Optimizing skin cancer screening with convolutional neural networks in smart healthcare systems
inferred← citeshttps://doi.org/10.17559/tv-20230614000735openalex-snapshot
The Adaptive Quadratic Linear Unit (AQuLU): Adaptive Non Monotonic Piecewise Activation Function
inferred← citeshttps://doi.org/10.17721/1812-5409.2025/1.16openalex-snapshot
Use of Izhikevich neurons in Hopfield models
inferred← citeshttps://doi.org/10.17721/2706-9699.2024.2.02openalex-snapshot
INFLUENCE OF CHAOS ON ACTIVATION FUNCTIONS IN HOPFIELD NETWORKS
inferred← citeshttps://doi.org/10.17780/ksujes.1760369openalex-snapshot
AUTOMATIC CLASSIFICATION SYSTEM FOR PERIAPICAL LESIONS WITH THE TOOTHNET CNN ARCHITECTURE INTEGRATING THE PROPOSED HYBRID ACTIVATION FUNCTION ON CBCT SCANS
inferred← citeshttps://doi.org/10.18280/isi.290321openalex-snapshot
Evaluation of UDP-Based DDoS Attack Detection by Neural Network Classifier with Convex Optimization and Activation Functions
inferred← citeshttps://doi.org/10.18517/ijaseit.13.4.18290openalex-snapshot
Mobile Skin Disease Classification using MobileNetV2 and NASNetMobile
inferred← citeshttps://doi.org/10.19072/ijet.1394093openalex-snapshot
The Impact of Irrationals on the Range of Arctan Activation Function for Deep Learning Models
inferred← citeshttps://doi.org/10.26877/asset.v6i1.17821openalex-snapshot
The Effect of LAB Color Space with NASNetMobile Fine-tuning on Model Performance for Crowd Detection
inferred← citeshttps://doi.org/10.30591/jpit.v8i3.5703openalex-snapshot
A Comparative Study of MobileNet Architecture Optimizer for Crowd Prediction
inferred← citeshttps://doi.org/10.3389/fsufs.2022.1073969openalex-snapshot
Adulteration detection in minced beef using low-cost color imaging system coupled with deep neural network
inferred← citeshttps://doi.org/10.3390/agriculture15242550openalex-snapshot
A Lightweight Segmentation Model for Northern Corn Leaf Blight Based on an Enhanced UNet Architecture
inferred← citeshttps://doi.org/10.3390/app13031928openalex-snapshot
Tree Species Classification Based on Self-Supervised Learning with Multisource Remote Sensing Images
inferred← citeshttps://doi.org/10.3390/app14052107openalex-snapshot
Device Position-Independent Human Activity Recognition with Wearable Sensors Using Deep Neural Networks
inferred← citeshttps://doi.org/10.3390/axioms12030246openalex-snapshot
NIPUNA: A Novel Optimizer Activation Function for Deep Neural Networks
inferred← citeshttps://doi.org/10.3390/diagnostics15182349openalex-snapshot
Two-Stage Hierarchical Pruning (THP-CNN) of Convolutional Neural Networks for Rapid Pathogenic Bacterial Detection Using High-Resolution Colony Images in Intensive Care Units
inferred← citeshttps://doi.org/10.3390/electronics11060937openalex-snapshot
IE-Net: Information-Enhanced Binary Neural Networks for Accurate Classification
inferred← citeshttps://doi.org/10.3390/electronics14234661openalex-snapshot
TRex: A Smooth Nonlinear Activation Bridging Tanh and ReLU for Stable Deep Learning
inferred← citeshttps://doi.org/10.3390/electronics15184325openalex-snapshot
A Novel Weight Initialization Scheme for Randomized Leaky Rectified Linear Units and a Comparative Analysis of Rectified Activation Functions for Image Classification
inferred← citeshttps://doi.org/10.3390/f13081284openalex-snapshot
Enhancing Height Predictions of Brazilian Pine for Mixed, Uneven-Aged Forests Using Artificial Neural Networks
inferred← citeshttps://doi.org/10.3390/f14061211openalex-snapshot
Semi-Supervised Tree Species Classification for Multi-Source Remote Sensing Images Based on a Graph Convolutional Neural Network
inferred← citeshttps://doi.org/10.3390/ijerph19137979openalex-snapshot
Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand
inferred← citeshttps://doi.org/10.3390/informatics13070118openalex-snapshot
Enhancing 3D MRI-Based Necrotic Core Segmentation in Glioblastoma Using Activation Functions in Deep Learning
inferred← citeshttps://doi.org/10.3390/polym16091204openalex-snapshot
Predicting Diffusion Coefficients in Nafion Membranes during the Soaking Process Using a Machine Learning Approach
inferred← citeshttps://doi.org/10.3390/pr13103053openalex-snapshot
Fire Resistance Prediction in FRP-Strengthened Structural Elements: Application of Advanced Modeling and Data Augmentation Techniques
inferred← citeshttps://doi.org/10.3390/rs16214073openalex-snapshot
Cross Attention-Based Multi-Scale Convolutional Fusion Network for Hyperspectral and LiDAR Joint Classification
inferred← citeshttps://doi.org/10.3390/rs16244617openalex-snapshot
A Comparative Study of Deep Learning Frameworks Applied to Coffee Plant Detection from Close-Range UAS-RGB Imagery in Costa Rica
inferred← citeshttps://doi.org/10.35234/fumbd.1881368openalex-snapshot
Integrating Local and Global Feature Learning for Retinal Disease Detection: An EfficientNetB3-ViT Hybrid Model
inferred← citeshttps://doi.org/10.3934/math.2024193openalex-snapshot
Conditional random k satisfiability modeling for k = 1, 2 (CRAN2SAT) with non-monotonic Smish activation function in discrete Hopfield neural network
inferred← citeshttps://doi.org/10.3934/mfc.2025009openalex-snapshot
ReLU-like non-monotonic smooth activation functions based on regularized heaviside functions and extensions
inferred← citeshttps://doi.org/10.46254/an12.20221019openalex-snapshot
THE EFFECT OF OPTIMIZERS ON SIAMESE NEURAL NETWORK PERFORMANCE
inferred← citeshttps://doi.org/10.7717/peerj-cs.2756openalex-snapshot
Activation function cyclically switchable convolutional neural network model
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.