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Papers tagged with "Convolution"
EPILEPSY PREDICTION USING CONVOLUTIONAL NEURAL NETWORK
This Paper Represents A Novel Design And Control Architecture Of The Continuous Stirred Tank Reactor (CSTR) Based On Its Mathematical Equivalent Modeling Of The Physical System. The Plant Is Formed Analytically For The Normal Operating Cond...
SWIFT DRAW : REAL-TIME DOODLE IDENTIFICATION USING CNN
Hand-drawn Doodle Recognition Has Significant Importance In The Real World. It Is Very Difficult And Hidius Task To Recognise The Hand-drawn Doodles.In This Paper I Use Convolution Neural Network To Recognise The Doodle Drawn By The User. U...
LUNG CANCER DETECTION USING MULTI-CLASS SVM AND CNN
Several New Approaches Has Been Used To Remove The Snap Blur Caused Due To The Camera Shake, With One Or More Multiple Images, By Providing Solutions For An Inverse And Inherently Illposed Deconvolution Problem. Currently, In All New Digita...
COLOR IMAGE ENHANCEMENT USING CNN
In This Paper, We Propose Perceptually Optimized Enhancement Of Contrast And Color In Images Using Convolution Neural Network (CNN). The Existing Image Enhancement Method Is Based On JND Transform To Estimate JND Map That Represents Percep...
VERY DEEP CONVOLUTIONAL NETWORKS AND RANDOM FOREST USED IN IMAGE PROCESSING TECHNIQUES
Here, We Inspect The Outcome Of The Convolutional Network Depth On Its Correctness In The Large-scale Image Recognition Tasks. The Chief Role Is Thorough Valuation Of Networks Of Increasing Deepness By Means Of An Architecture With Small (...
VIDEO ANALYSIS OF HUMAN POSE ESTIMATION USING DEEP NEURAL NETWORKS AND COMPUTER VISION APPROACHES AND ITS APPLICATIONS
Deep Architectures With Convolution Structure Have Been Found Highly Effective And Commonly Used In Computer Vision. With The Introduction Of Graphics Processing Unit (GPU) For General Purpose Issues, There Has Been An Increasing Attention...
RECOGNITION OF VINDICTIVE CODE VARIATIONS DEPENDENT ON DEEP LEARNING
With The Improvement Of The Web, Malignant Code Assaults Have Expanded Exponentially, With Vindictive Code Variations Positioning As A Key Danger To Web Security. The Capacity To Identify Variations Of Vindictive Code Is Basic For Insurance...
SINGLE IMAGE HAZE REMOVAL METHOD USING CONDITIONAL RANDOM FIELDS
To Enhance The Visibility, Saturation, Contrast And Reduce The Noise In A Foggy Image. Outdoor Scenes Are Often Affected By Fog, Haze Or Smog. To Capture Such Landscapes As Fog Or Haze Adds Significant Visual Pull. Fog And Haze Degrade The...
REVIEW ON LEAF DISEASE DETECTING USING CNN TECHNIQUE
Leaf Illness Identification Requires Enormous Measure Of Work, Information In The Plant Maladies, And Requires The All The More Handling Time. We Have Proposed Framework Has Used To Structure And Usage Digital Picture Handling Methods For D...
Driver Distraction Detection using Neural Network
Distracted Driving Is Known To Be The Leading Cause Of Motor Vehicle Accidents. It Is Found That Nearly One In Five Motor Vehicle Accidents Were Caused By Distracted Driving. Motivated To Reduce These Number Of Accidents, The Purpose Of Thi...
A REVIEW OF DETECTION OF HEART FAILURE USING DEEP LEARNING TECHNIQUES
One Of The Major Reasons For Deaths, Not Only In India But All Over The World Is Cardiovascular Diseases. Every Year, Almost A Million People Die Due To These Heart Diseases. In This Study, We Will Be Focusing On Heart Failure (or Congestiv...
DEEP LEARNING USING TILED CONVOLUTION FEATURE EXTRACTION TECHNIQUE FOR CONTENT-BASED IMAGE RETRIEVAL
In The Last Few Years, Deep Learning Has Led To Very Good Performance On A Variety Of Problems, Such As Visual Recognition, Speech Recognition And Natural Language Processing. Deep Learning Using Tiled Convolution Feature Extraction Techniq...
A review on the Performance of Turbo Encoder/Decoder
In This Paper, Turbo Encoder Is Designed Using The Parallel Link Of Two Convolution Encoder Which Is Isolated By Interleaver. Turbo Codes Assume In Pivotal Job In Various Application For Instance Portable Radio, Modernized Video, Remote Sat...
SHADOW DETECTION USING CONVOLUTIONAL NEURAL NETWORK
We Present A Practical Framework To Automatically Detect Shadows In Real-world Scenes From A Single Photograph Previous Works On Shadow Detection Requires Human Intervention To Detect Shadow.But Our Framework Automatically Learns The Most R...
AN IMAGE CLASSIFICATION BASED ON CNN APPROACH FOR PLANT LEAF DISEASE DETECTION
This Paper Provides Survey On Plant Leaf Disease Detection Using Machine Learning Techniques. As Disease In Plants Makes Significant Impact On Production In Agriculture Finding This Diseases In An Early Stage Is Difficult Thing As Farmers A...