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Particle Swarm Optimization for Automatically Evolving Convolutional Neural Networks for Image Classification

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A Survey on Deep Transfer Learning
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A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification
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Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition
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Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems
inferredcites →https://doi.org/10.1007/s11721-007-0002-0openalex-snapshot
Particle swarm optimization
inferredcites →https://doi.org/10.1016/b978-0-12-416743-8.00008-7openalex-snapshot
Firefly Algorithms
inferredcites →https://doi.org/10.1016/j.advengsoft.2013.12.007openalex-snapshot
Grey Wolf Optimizer
inferredcites →https://doi.org/10.1016/j.asoc.2017.03.024openalex-snapshot
Intelligent leukaemia diagnosis with bare-bones PSO based feature optimization
inferredcites →https://doi.org/10.1016/j.asoc.2019.105725openalex-snapshot
Intelligent skin cancer diagnosis using improved particle swarm optimization and deep learning models
inferredcites →https://doi.org/10.1016/j.jocs.2020.101104openalex-snapshot
Nature-inspired optimization algorithms: Challenges and open problems
inferredcites →https://doi.org/10.1016/j.knosys.2019.06.015openalex-snapshot
Adaptive melanoma diagnosis using evolving clustering, ensemble and deep neural networks
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A region-based image caption generator with refined descriptions
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A GPSO-optimized convolutional neural networks for EEG-based emotion recognition
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A hierarchical and regional deep learning architecture for image description generation
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Anomaly detection with convolutional neural networks for industrial surface inspection
inferredcites →https://doi.org/10.1016/j.swevo.2019.05.010openalex-snapshot
Particle swarm optimization of deep neural networks architectures for image classification
inferredcites →https://doi.org/10.1016/j.swevo.2019.06.002openalex-snapshot
cPSO-CNN: An efficient PSO-based algorithm for fine-tuning hyper-parameters of convolutional neural networks
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/access.2018.2880416openalex-snapshot
Evolving Image Classification Architectures With Enhanced Particle Swarm Optimisation
inferredcites →https://doi.org/10.1109/access.2019.2903015openalex-snapshot
Evolving Ensemble Models for Image Segmentation Using Enhanced Particle Swarm Optimization
inferredcites →https://doi.org/10.1109/access.2020.2964424openalex-snapshot
Neural Architecture Search for Skin Lesion Classification
inferredcites →https://doi.org/10.1109/cec.2018.8477735openalex-snapshot
Evolving Deep Convolutional Neural Networks by Variable-Length Particle Swarm Optimization for Image Classification
inferredcites →https://doi.org/10.1109/cec48606.2020.9185541openalex-snapshot
Particle Swarm optimisation for Evolving Deep Neural Networks for Image Classification by Evolving and Stacking Transferable Blocks
inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot
Going deeper with convolutions
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-snapshot
You Only Look Once: Unified, Real-Time Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-snapshot
Densely Connected Convolutional Networks
inferredcites →https://doi.org/10.1109/cvpr.2018.00907openalex-snapshot
Learning Transferable Architectures for Scalable Image Recognition
inferredcites →https://doi.org/10.1109/iccv.2015.169openalex-snapshot
Fast R-CNN
inferredcites →https://doi.org/10.1109/icmew.2018.8551564openalex-snapshot
Fall Detection Using Convolutional Neural Network With Multi-Sensor Fusion
inferredcites →https://doi.org/10.1109/icnn.1995.488968openalex-snapshot
Particle swarm optimization
inferredcites →https://doi.org/10.1109/ijcnn.2019.8852369openalex-snapshot
Evolving and Ensembling Deep CNN Architectures for Image Classification
inferredcites →https://doi.org/10.1109/nabic.2009.5393690openalex-snapshot
Cuckoo Search via Lévy flights
inferredcites →https://doi.org/10.1109/tcyb.2016.2549639openalex-snapshot
A Micro-GA Embedded PSO Feature Selection Approach to Intelligent Facial Emotion Recognition
inferredcites →https://doi.org/10.1109/tcyb.2020.2983860openalex-snapshot
Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification
inferredcites →https://doi.org/10.1109/tevc.2018.2808689openalex-snapshot
Evolving Unsupervised Deep Neural Networks for Learning Meaningful Representations
inferredcites →https://doi.org/10.1109/tevc.2019.2916183openalex-snapshot
Evolving Deep Convolutional Neural Networks for Image Classification
inferredcites →https://doi.org/10.1109/tkde.2009.191openalex-snapshot
A Survey on Transfer Learning
inferredcites →https://doi.org/10.1109/tnnls.2019.2919608openalex-snapshot
Completely Automated CNN Architecture Design Based on Blocks
inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-snapshot
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
inferredcites →https://doi.org/10.1109/tpami.2018.2844175openalex-snapshot
Mask R-CNN
inferredcites →https://doi.org/10.1145/1273496.1273556openalex-snapshot
An empirical evaluation of deep architectures on problems with many factors of variation
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.4230/oasics.dx.2026.15openalex-snapshot
AutoResearch Lite: a reproducible paper-inspired experiment runner (Adam mechanism reproduction and convergence-speed comparison)
inferredcites →https://doi.org/10.4230/oasics.ng-res.2024.2openalex-snapshot
A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control (Invited Paper)
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot
Adam: A Method for Stochastic Optimization
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.1611.02167openalex-snapshot
Designing Neural Network Architectures using Reinforcement Learning
inferredcites →https://doi.org/10.48550/arxiv.1804.02767openalex-snapshot
YOLOv3: An Incremental Improvement
inferredcites →https://doi.org/10.48550/arxiv.1806.09055openalex-snapshot
DARTS: Differentiable Architecture Search
inferredcites →https://doi.org/10.48550/arxiv.1810.11530openalex-snapshot
Automatic differentiation in ML: Where we are and where we should be going
inferredcites →https://doi.org/10.5244/c.30.87openalex-snapshot
Wide Residual Networks
inferredcites →https://doi.org/10.7551/mitpress/1090.001.0001openalex-snapshot
Adaptation in Natural and Artificial Systems
inferredcites →https://doi.org/10.7551/mitpress/3927.001.0001openalex-snapshot
An Introduction to Genetic Algorithms

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Attention Deep Neural Networks with Bayesian Hyper-Parameter Optimization for Short-Term Load Forecasting
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