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Papers tagged with "Classification"
Fraud Detection And Analysis For Insurance Claims Using Machine Learning
Insurance Fraud, Particularly In Claim Processing, Results In Billions Of Dollars In Losses Annually For Companies Worldwide. Manual And Rule-based Detection Mechanisms Are Often Inefficient In Detecting Sophisticated Fraud Schemes. This St...
A Review On Machine Learning Based Models For Identifying Potential Adversarial And Poisoning Attacks
Machine Learning (ML) Has Revolutionized Data-driven Decision-making Across Sectors Such As Healthcare, Finance, Defense, And Cybersecurity. However, As Its Influence Grows, So Does Its Vulnerability To Adversarial And Poisoning Attacks. Ad...
A Comprehensive Review On Machine Learning Based Techniques For Crop Blight Detection
Plant Diseases Like Early And Late Blight Must Be Promptly Identified, And This Requires Automated Blight Detection. These Illnesses Have The Potential To Spread Quickly And Seriously Harm Crops. By Taking Timely And Focused Action To Limit...
A Review On Natural Language Processing Techniques For Sentiment Analysis Of Potentially Radical And Hateful Content On Social Media
Natural Language Processing Has A Large Number Of Applications Especially For Semantic Web. This Study Provides A Comprehensive Assessment Of Contemporary Machine Learning And Deep Learning Algorithms For Hate Speech Identification. Example...
MARINE SPECIES RECOGNITION USING IMAGE ANALYSIS
The Identification And Classification Of Marine Species Play A Vital Role In Ecological Studies, Biodiversity Protection, And Sustainable Fisheries Management. Traditional Approaches That Rely On Manual Observation Are Not Only Time-intensi...
Service Usage Classification With Encrypted Internet Traffic In Moblie Messaging Apps
The Rapid Adoption Of Mobile Messaging Apps Has Enabled Us To Collect Massive Amount Of Encrypted Internet Traffic Of Mobile Messaging. The Classification Of This Traffic Into Different Types Of In-App Service Usages Can Help For Intelligen...
Silent Alert: Advancing Women's Security Through Smart Sign Recognition And AI
Women's Safety Is A Global Concern Requiring Immediate And Innovative Solutions. This Paper Introduces "Silent Alert," A Real-time Hand Gesture Recognition System That Detects Emergency And Rescue Signs Based On Video Input. Leveraging Medi...
ALERTDRIVER: EARLY DETECTION OF FATIGUE STATES IN DRIVERS DURING LONG DRIVING STRETCHES
The Majority, Of The Accidents Were Happening Perpetually Due To Driver Drowsiness Over The Decades. Automation Has Been Playing Key Role In Many Fields To Provide Conformity And Improve The Quality Of Life Of The Users. Though Various Drow...
Intelligent Fault Diagnosis In Cascaded Multilevel Inverters Using Multiscale Kernel CNN
This Paper Proposes An Intelligent Fault Diagnosis Method For Cascaded Multilevel Inverters Using A Multiscale Kernel Convolutional Neural Network (CNN). The Approach Leverages The Ability Of CNNs To Extract Features From Signals And Diagno...
A Deep Learning Driven Approach For Automated Identification And Classification Of Defects In Printed Circuit Boards
In The Fast-paced Electronics Manufacturing Industry, Ensuring The Quality Of Printed Circuit Boards (PCBs) Is Essential For Producing Reliable And High-performance Devices. Traditional Methods For PCB Defect Detection, Such As Manual Visua...
AI Based Neural Network Model For Stroke Prediction
Many Individuals Encounter Situations Where They Need Basic Legal Information And Guidance. However, Obtaining Professional Legal Advice Can Be Prohibitively Expensive, Especially For Minor Issues Or General Inquiries. As Technology Continu...
SUSTAINABLE AGRICULTURE: A APPROACH FOR RICE LEAF DISEASE DETECTION AND CLASSIFICATION USING DCNN AND ENHANCED DATASETS
The Quality And Productivity Of Rice Crops Can Be Significantly Impacted By A Variety Of Diseases. For Effective Management And Higher Agricultural Productivity, Early Disease Detection And Classification Are Essential. The Primary Objectiv...
Brain Tumer Detection Using Machine Learning
Brain Tumors Result From The Abnormal And Uncontrolled Growth Of Cells. If Left Untreated During The Early Stages, They Can Become Life-threatening. Although Numerous Significant Advancements Have Been Achieved In This Field, Ensuring Accur...
RNN-Based Heartbeat Sound Analysis With Django Integration
Congenital Heart Diseases (CHDs) Are Among The Leading Causes Of Mortality Worldwide, Necessitating Early And Accurate Detection Methods.Improving Patient Outcomes And Facilitating Prompt Medical Intervention Depend Heavily On Early Diagnos...
EARLY DETECTION OF BRAIN STROKE FOR MEDICAL IMAGING THROUGH CNN AND IMAGE ANALYSIS
The Early Detection Of Brain Strokes Is Critical For Improving Patient Outcomes And Minimizing Long-term Disabilities. Timely Diagnosis Can Significantly Reduce The Risk Of Brain Damage By Enabling Swift Medical Intervention. This Research...