Diabetic Retinopathy Detection Using Machine Learning
Volume-4 | Issue-1

Monocular Depth Estimation using a Multi-grid Attention-based Model
Volume-4 | Issue-3

Speedy Image Crowd Counting by Light Weight Convolutional Neural Network
Volume-3 | Issue-3

Construction of Efficient Smart Voting Machine with Liveness Detection Module
Volume-3 | Issue-3

An Economical Robotic Arm for Playing Chess Using Visual Servoing
Volume-2 | Issue-3

Triplet loss for Chromosome Classification
Volume-4 | Issue-1

Unstructured Noise Removal for Industrial Sensor Imaging Unit by Hybrid Adaptive Median Algorithm
Volume-3 | Issue-4

Nighttime Rainy Season Traffic Analysis: Vehicle Detection, Tracking, and Counting with YOLOv8 and DeepSORT
Volume-5 | Issue-3

Real Time Sign Language Recognition and Speech Generation
Volume-2 | Issue-2

Analysis of Artificial Intelligence based Image Classification Techniques
Volume-2 | Issue-1

A REVIEW ON IOT BASED MEDICAL IMAGING TECHNOLOGY FOR HEALTHCARE APPLICATIONS
Volume-1 | Issue-1

COMPUTER VISION BASED TRAFFIC SIGN SENSING FOR SMART TRANSPORT
Volume-1 | Issue-1

Diabetic Retinopathy Detection Using Machine Learning
Volume-4 | Issue-1

Accurate Segmentation for Low Resolution Satellite images by Discriminative Generative Adversarial Network for Identifying Agriculture Fields
Volume-3 | Issue-4

Deep Learning based Handwriting Recognition with Adversarial Feature Deformation and Regularization
Volume-3 | Issue-4

State of Art Survey on Plant Leaf Disease Detection
Volume-4 | Issue-2

Optimal Compression of Remote Sensing Images Using Deep Learning during Transmission of Data
Volume-3 | Issue-4

OverFeat Network Algorithm for Fabric Defect Detection in Textile Industry
Volume-3 | Issue-4

VIRTUAL RESTORATION OF DAMAGED ARCHEOLOGICAL ARTIFACTS OBTAINED FROM EXPEDITIONS USING 3D VISUALIZATION
Volume-1 | Issue-2

Two-Stage Frame Extraction in Video Analysis for Accurate Prediction of Object Tracking by Improved Deep Learning
Volume-3 | Issue-4

Home / Archives / Volume-3 / Issue-1 / Article-6

Volume - 3 | Issue - 1 | march 2021

A Study to Find Facts Behind Preprocessing on Deep Learning Algorithms
Pages: 66-74
DOI
10.36548/jiip.2021.1.006
Published
27 April, 2021
Abstract

In the near future, deep learning algorithms will be incorporated in several applications for assisting the human beings. The deep learning algorithms have the tendency to allow a computer to work on its assumption. Most of the deep learning algorithms mimic the human brain's neuron connection to leverage an artificial intelligence to the computer system. This helps to improve the operational speed and accuracy on several critical tasks. This paper projects the blocks, which are required for the incorporation of deep learning based algorithm. Also, the paper attempts to deeply analyze the necessity of the preprocessing step over several deep learning based applications.

Keywords

Preprocessing image data signal text classification EEG ECG EMG

×

Currently, subscription is the only source of revenue. The subscription resource covers the operating expenses such as web presence, online version, pre-press preparations, and staff wages.

To access the full PDF, please complete the payment process.

Subscription Details

Category Fee
Article Access Charge
15 USD
Open Access Fee 100 USD
Annual Subscription Fee
200 USD
After payment,
please send an email to irojournals.contact@gmail.com / journals@iroglobal.com requesting article access.
Subscription form: click here