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Papers tagged with "Neural"
ForestGuard AI: Acoustic Detection Of Chainsaw Activity For Illegal Logging Monitoring
Illegal Logging Is A Major Environmental Problem That Affects Forest Ecosystems, Biodiversity, And Natural Resources. Conventional Forest Monitoring Techniques Based Mainly On Manual Patrols And Visual Inspection Can Be Difficult To Scale A...
An Interpretable Deep Learning Framework For MRI-Based Alzheimer’s Disease Detection And Automated Clinical Reporting
Alzheimer’s Disease (AD) Is A Progressive Neurodegenerative Disorder That Affects Memory, Cognitive Abilities, And Overall Brain Function, Particularly In The Aging Population. Early And Reliable Diagnosis Is Essential For Timely Interventi...
A Comprehensive Review On Machine Learning And Deep Learning Models For Forecasting Stock Market Trends
Machine Learning Is Transforming Stock Market Prediction By Leveraging Vast Datasets, Advanced Algorithms, And Computational Power To Provide More Accurate Forecasts. While Challenges Remain, Continuous Advancements In Artificial Intelligen...
Defect Detection In Printed Circuit Board Using CNN
The Physical Violence Detection Using Key Framing Printed Circuit Board (PCB) Inspection Is An Essential Part Of PCB Production Process. Traditional PCB Bare Board Defect Detection Methods Have Their Own Defects. However, The PCB Bare Board...
A Review On Machine Learning Enabled MIMO Systems For Capacity Enhancement In Wireless Networks
Due To Increasing Number Of Users And Multimedia Applications, Multiple Input, Multiple Output (MIMO) Systems Have Become Indispensable From Wireless Technology. The Benefit Of MIMO Systems Is Increase In The Channel Capacity At Low Bandwid...
Brain Tumor Detection From MRI Scans Using Convolutional Neural Networks
Brain Tumors Are Among The Most Life-threatening Neurological Disorders That Require Early And Accurate Diagnosis To Improve Patient Survival And Treatment Outcomes. Magnetic Resonance Imaging (MRI) Is Widely Used For Detecting Brain Abnorm...
Brain Tumor Detection From MRI Scans Using Convolutional Neural Networks: A Review
Brain Tumor Detection Is One Of The Most Critical Applications Of Artificial Intelligence (AI) In Medical Image Analysis. Early And Accurate Identification Of Brain Tumors Plays A Vital Role In Improving Patient Survival Rates And Assisting...
An Optimized Deep Learning Model For Churn Rate Prediction
Data Science And Machine Learning Are Being Used Extensively For Business Analytics. One Of The Major Applications Happens To Be Estimating Churn And Attrition Rates. In Today’s Competitive Market Landscape, Retaining Customers Is As Crucia...
A Deep Learning Approach For Predicting Crypto Currency Prices Trends
Machine Learning And Deep Learning Models Are Being Extensively Used At The Backend Of Forecasting Crypto Prices. Many Factors, Including Changes In Regulation, Public Opinion On Social Media, Investor Actions, And Overall Global Economic T...
A Comprehensive Review On Contemporary Machine Learning And Deep Learning Models For Forecasting Stock Market Trends
Machine Learning Is Transforming Stock Market Prediction By Leveraging Vast Datasets, Advanced Algorithms, And Computational Power To Provide More Accurate Forecasts. While Challenges Remain, Continuous Advancements In Artificial Intelligen...
Physical Violence Detection Using Key Framing
The Physical Violence Detection Using Key Framing App Is An AI-based Android Application Designed To Detect Violent Activities From Video Footage Using Intelligent Frame Analysis. The System Focuses On Identifying Suspicious Physical Action...
Speech Stress Detection In Marathi And SUSAS Databases Using Weight-Optimized Neural Networks
Stress Profoundly Alters Human Cognitive And Physiological States, Making Early And Automated Detection A Critical Technological Goal [1]. This Study Presents A Streamlined Speech Emotion Recognition (SER) System Engineered For Accurate Str...
AI Cardiologist: Advancements In Supervised Learning For Heart Disease Prediction
Cardiovascular Disease (CVD) Continues To Pose A Significant Global Health Challenge, Demanding Innovative Approaches For Early Detection And Prevention. This Paper Presents An AI Cardiologist System That Leverages Supervised Machine Learni...
AIML-Based Quality Assurance System For Agricultural Products Using Tensorflow
Agricultural Product Quality Assessment Plays A Critical Role In The Global Food Supply Chain, Directly Impacting Market Pricing, Consumer Safety, And Post-harvest Optimization. Traditional Methods Rely Heavily On Human Vision And Manual So...
BuySense: A Dual-Model Approach For Purchase Viability Prediction Using Amazon Review Data
This Paper Presents The BuySense, A Machine Learning Application That Predicts Whether A Product Is Worth Purchasing Based On Amazon Review Text Data. The System Builds Two Independent Binary Classifiers—a Viability Model And A Regret Model...