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Papers tagged with "Image Classification"
Embedded Edge-AI Framework For Autonomous UAV-Based Human Detection And Remote Alerting Using ESP32-S3 Flight Control And ESP32-CAM Vision
Autonomous Unmanned Aerial Vehicles (UAVs) Equipped With On-board Artificial-intelligence Inference Are Increasingly Used For Surveillance And Monitoring Tasks That Require Rapid, Low-latency Decisions Without Continuous Human Supervision....
AgroNGO: A Machine Learning–Enabled Platform For Farm-to-Consumer Commerce And Sustainable Food Redistribution
A Major Challenge That The Agriculture Supply Chain Is Facing In India Is The Lack Of Technology. Fragmented With Large Losses In Food Post Harvest, Lowering Farmers' Income, Poor Food Availability For Low-income Groups. This Paper Outlines...
Real-Time Detection Of Forest Fires Using FireNet-CNN And Explainable AI Techniques
This Study Proposes FireNet-CNN, A Lightweight And Efficient Deep Learning Model For Real-time Forest Fire Detection Using Convolutional Neural Networks (CNN) And Explainable AI (XAI) Techniques. The Model Was Trained And Evaluated On Augme...
Explainable Deep Neural Network Based Multiclass Classification Of Tomato Leaf Disease
Tomato Leaf Diseases Pose A Persistent Challenge To Sustainable Crop Production, Requiring Accurate And Computationally Efficient Diagnostic Solutions For Real-time Field Applications. This Study Proposes A Hybrid Deep Learning Framework Th...
BIOSIGNAL SMOCKING DETECTION OF X-RAY IMAGES
Lung Diseases Such As Viral Pneumonia And Smoking-induced Lung Damage Are Major Global Health Concerns Responsible For Millions Of Deaths Each Year. Early And Accurate Detection Of These Conditions Is Essential For Timely Medical Interventi...
ENHANCED GASTROINTESTINAL DISEASE DETECTION USING RESNET50: A COMPARATIVE STUDY OF DEEP LEARNING ARCHITECTURES FOR MEDICAL IMAGE CLASSIFICATION
Gastrointestinal (GI) Diseases Such As Polyps, Ulcers, And Tumors Require Early Detection For Effective Treatment. Traditional Manual Inspection Of Endoscopy Images Is Timeconsuming And Prone To Human Error. This Project Proposes An AIbased...
AN INTELLIGENT MULTI-ALGORITHM MACHINE LEARNING SYSTEM FOR SKIN DISEASE CLASSIFICATION AND PREDICTION
This Paper Proposes An Interpretable And Explainable Multi-class Skin Lesion Classification Model For The HAM10000 Dataset. Timely Detection Of Skin Cancer Is Important But Difficult Due To Class Imbalance And Uninterpretability Of Current...
Enhanced ODIRNet: Attention-Driven And Explainable Deep Neural Network For Robust Diabetic Retinopathy Detection
Diabetic Retinopathy (DR) Is A Significant Global Health Concern, Especially In Areas With High Rates Of Diabetes. Early Detection Via Automated Systems Can Reduce The Risk Of Blindness. This Paper Introduces ODIRNet, A Compact Deep Convolu...
Detection of Diabetic Retinopathy Using a Multi-Decision Inception-ResNet Blended Hybrid Model
Diabetic Retinopathy (DR) Represents A Critical Complication Of Diabetes Mellitus, Leading To Progressive Vision Impairment And Potential Blindness If Left Undetected. This Research Presents A Novel Multi-decision Inception-ResNet Blended H...
DEEPTRACENET: AN AI DRIVEN FRAMEWORK FOR MATHEMATICAL FEATURE-BASED FORGERY DETECTION
The Rapid Growth Of Deepfake Technologies Has Raised Serious Concerns Regarding The Authenticity Of Digital Images And Videos, Impacting Information Security, Media Credibility, And Forensic Analysis. This Research Presents A Deep Learning-...
Plant Disease Detection Using Deep Learning
Agriculture Plays A Crucial Role In Global Food Security, And Plant Diseases Represent One Of The Most Significant Threats To Crop Productivity And Quality Worldwide. Traditional Methods Of Disease Identification Rely Heavily On Manual Insp...
LUNG TUMOR SEGMENTATION USING VISUAL GEOMETRY GROUP NETWORKS IN MRI IMAGES
Lung Cancer Is One Of The Most Life-threatening Diseases Worldwide, And Early Diagnosis Significantly Increases The Chances Of Survival. Accurate Detection And Classification Of Lung Tumors Remain Challenging Due To Variations In Tumor Size...
Handwritten Digit Recognition Using Convolutional Neural Networks (CNN) On The MNIST Dataset
Handwritten Digit Recognition Is Crucial In Various Automated Tasks Like Financial Verification, Postal Sorting, And Digital Form Processing, Where Correctly Understanding Handwritten Numbers Is Key. This Study Looks At How Well Convolution...
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...
Early-Stage Oral Cancer Identification Using White Light Imaging And LightGBM Algorithm
Oral Cancer Is A Significant Public Health Concern Globally, With Early Detection Playing A Crucial Role In Improving Patient Outcomes. In This Project, We Propose A Novel Approach For Oral Cancer Detection Leveraging Deep Learning Techniqu...