An Introduction to Convolutional Neural Networks

Abstract

The field of machine learning has taken a dramatic twist in recent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models are able to far exceed the performance of previous forms of artificial intelligence in common machine learning tasks. One of the most impressive forms of ANN architecture is that of the Convolutional Neural Network (CNN). CNNs are primarily used to solve difficult image-driven pattern recognition tasks and with their precise yet simple architecture, offers a simplified method of getting started with ANNs. This document provides a brief introduction to CNNs, discussing recently published papers and newly formed techniques in developing these brilliantly fantastic image recognition models. This introduction assumes you are familiar with the fundamentals of ANNs and machine learning.

10 pages, 5 figures

References in corpus (2)

• Improving neural networks by preventing co-adaptation of feature detectors
• Stochastic Pooling for Regularization of Deep Convolutional Neural Networks

Cited by in corpus (47)

• All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda
• Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey
• Digital Electronics and Analog Photonics for Convolutional Neural Networks (DEAP-CNNs)
• Adversarial Example Detection for DNN Models: A Review and Experimental Comparison
• Gas Detection and Identification Using Multimodal Artificial Intelligence Based Sensor Fusion
• Review: Deep Learning in Electron Microscopy
• Quantum Algorithms for Deep Convolutional Neural Networks
• Signal Processing and Machine Learning Techniques for Terahertz Sensing: An Overview
• Detection and Classification of Supernova Gravitational Waves Signals: A Deep Learning Approach
• Handwritten Digit Recognition using Machine and Deep Learning Algorithms
• Automatic extraction of road intersection points from USGS historical map series using deep convolutional neural networks
• Real-time Plant Health Assessment Via Implementing Cloud-based Scalable Transfer Learning On AWS DeepLens
• Quiver Mutations, Seiberg Duality and Machine Learning
• Artificial Intelligence in the Autonomous Navigation of Endovascular Interventions: A Systematic Review
• TrackMPNN: A Message Passing Graph Neural Architecture for Multi-Object Tracking
• Human Activity Recognition using Continuous Wavelet Transform and Convolutional Neural Networks
• StoManager1: An Enhanced, Automated, and High-throughput Tool to Measure Leaf Stomata and Guard Cell Metrics Using Empirical and Theoretical Algorithms
• Homogeneous vector bundles and $G$-equivariant convolutional neural networks
• Machine learning-based classification for Single Photon Space Debris Light Curves
• Structural Health Monitoring of Cantilever Beam, a Case Study -- Using Bayesian Neural Network AND Deep Learning
• HyperNOMAD: Hyperparameter optimization of deep neural networks using mesh adaptive direct search
• A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and Datasets
• Visual design intuition: Predicting dynamic properties of beams from raw cross-section images
• Do Images really do the Talking? Analysing the significance of Images in Tamil Troll meme classification
• Random forests for detecting weak signals and extracting physical information: a case study of magnetic navigation
• ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER
• Classification of Brainwave Signals Based on Hybrid Deep Learning and an Evolutionary Algorithm
• ResAtom System: Protein and Ligand Affinity Prediction Model Based on Deep Learning
• Unbiased Subdata Selection for Fair Classification: A Unified Framework and Scalable Algorithms
• A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformers
• Relative gradient optimization of the Jacobian term in unsupervised deep learning
• Contextual Text Embeddings for Twi
• Understanding Information Spreading Mechanisms During COVID-19 Pandemic by Analyzing the Impact of Tweet Text and User Features for Retweet Prediction
• Signal-background separation and energy reconstruction of gamma rays using pattern spectra and convolutional neural networks for the Small-Sized Telescopes of the Cherenkov Telescope Array
• Unsupervised detection and open-set classification of fast-ramped flexibility activation events
• LW-GCN: A Lightweight FPGA-based Graph Convolutional Network Accelerator
• Testing and Emulating Modified Gravity on Cosmological Scales
• MILR: Mathematically Induced Layer Recovery for Plaintext Space Error Correction of CNNs
• Nonparametric signal separation in very-high-energy gamma ray observations with probabilistic neural networks
• Reconstructing High-resolution Turbulent Flows Using Physics-Guided Neural Networks
• Convolutional Neural Network with Pruning Method for Handwritten Digit Recognition
• Enacted Visual Perception: A Computational Model based on Piaget Equilibrium
• UIT-HWDB: Using Transferring Method to Construct A Novel Benchmark for Evaluating Unconstrained Handwriting Image Recognition in Vietnamese
• Quantum Algorithms for Unsupervised Machine Learning and Neural Networks
• The human visual system and CNNs can both support robust online translation tolerance following extreme displacements
• Automatic Task Requirements Writing Evaluation via Machine Reading Comprehension
• A survey on deep learning approaches for breast cancer diagnosis