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Papers tagged with "Convolution"
Dental Disease Detection Based On Deep Learning Algorithm Using Various Radiographs
Dental Diseases Such As Dental Caries, Periodontal Disease, Periapical Lesions, And Bone Loss Are Among The Most Prevalent Oral Health Issues Globally. Early And Accurate Detection Is Critical To Preventing Progression And Ensuring Effectiv...
Brain Tumor Disease Detection Using Federated Learning With FedAvg
Federated Learning (FL) Has Emerged As A Critical Paradigm For Collaborative Model Training In Privacy-constrained Domains, Particularly In Healthcare. This Study Presents A Comprehensive FedAvg-based Framework For Brain Tumor Detection Fro...
Deep Learning Approaches For Brain State Detection Under Anesthesia: A CNN-LSTM Framework
This Research Presents An Automated Approach To Analyzing Brain States During Anesthesia Using Convolutional Neural Networks (CNNs) And Long Short-Term Memory (LSTM) Networks. By Leveraging The Spatial Feature Extraction Power Of CNNs And T...
A Convolutional Neural Network Approach To Interview Simulation And Evaluation
Artificial Intelligence (AI) Is Transforming A Wide Range Of Industries By Enabling Machines To Perform Tasks That Traditionally Required Human Intelligence, Such As Perception, Decision-making, And Natural Interaction. In The Context Of Re...
HELMET DETECTION AND NUMBER PLATE USING DEEP LEARNING
Individuals Frequently Disregard How Important It Is To Wear Helmets, Which Is Tragic. A Helmet Reduces Your Risk Of Getting A Serious Brain Injury And Dying By Deflecting Most Of The Impact Energy That Would Otherwise Hit Your Head And...
Breast Cancer Detection Using Hybrid Ri-Vit In Histopathalogical Images
Breast Cancer Remains A Significant Global Health Concern, Impacting Millions Of Women Each Year. Timely Detection And Precise Diagnosis Are Essential To Enhancing Treatment Success And Lowering Death Rates. Histopathological Imaging Is Wid...
An Improved Fire Detection Method Based On CNN
In Order To Minimize Damage, Fire Detection Is A Crucial Component Of Early Warning Systems In Both Urban And Rural Areas. And Quickening Response Times. Traditional Fire Detection Methods Have Limited Environmental Detecting Capabilitie...
Position-Sensitive Neural Networks For Insect Detection And Grain Quality Prediction In Storage
Insect Infestations In Grain Can Lead To Significant Losses In Both Quantity And Quality, Impacting Crop Value. These Insects Not Only Consume Grain But Also Contaminate It With Their Metabolic By-products And Body Parts, Contributing To Th...
AI-Powered Based Blind And Visually Impaired System For Smart Glass
Visual Impairment Poses Significant Challenges To The Daily Lives And Mobility Of Millions Of People Worldwide. In This Context, Smart Assistive Technologies Have Gained Momentum In Improving The Independence And Quality Of Life For The Bli...
Fetus Brain Tumor Detection Using Ultrasound Images In Deep Learning
The Early Identification Of Brain Tumors In Fetus Is Critical For Timely Medical Intervention And Improved Neonatal Outcomes. This Study Presents A Deep Learning-based Approach To Automatically Detect And Classify Brain Tumors In Fetal Ultr...
ECG PEAK DETECTION USING DEEP LEARNING APPROACHES
Cardiovascular Diseases (CVDs) Remain A Leading Cause Of Mortality Worldwide, Necessitating Efficient Diagnostic Tools For Early Detection. Electrocardiogram (ECG) Analysis Is A Cornerstone Of Cardiac Diagnosis, But Manual Interpretation Is...
DDOS DETECTION IN SOFTWARE DEFINED NETWORK USING FEDERATED LEARNING
Distributed Denial Of Service Attacks Have Become A Great Concern For Security In Software Defined Networking(SDN), As They Mostly Overload Centralized Security Mechanisms. In This Work, A Federated Learning-Based Intrusion Detection System...
DETECT GENUINE AND COUNTERFEIT LOGOS USING A CNN WITH THE INCEPTION V3 PRE TRAINED MODEL TO ACHIEVE HIGH ACCURACY
The Proliferation Of Counterfeit Products Poses Significant Challenges To Brand Integrity And Consumer Trust. This Paper Presents A Comprehensive Survey On Detecting Genuine And Counterfeit Logos Using Convolutional Neural Networks (CNNs) W...
A STUDY ON TYPE 2 DIABETES PREDICTION USING DEEP LEARNING TECHNIQUES
T2DM, Or Type 2 Diabetes Mellitus, Has Become A Major Global Health Concern Due To Its High Prevalence And Related Medical Expenses. With An Emphasis On Data-driven Strategies That Make Use Of Patient Health Information, Such As Blood Sugar...
A Study On Predicting House Prices With Deep Learning: An Evaluation Of Advanced Neural Network Models
Everyone Dreams Of Owning A Home That Aligns With Their Lifestyle And Meets Their Unique Needs, Including Essential Amenities. Factors Like Area, Location, And Views Play A Major Role In Determining The Price Of A House. However, Predicting...