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Papers tagged with "Resnet"
Enhanced Deepfake Detection Using ResNet50 And Facial Landmark Analysis
This Research Focuses On Accuracy Enhancement In The Detection Of Deepfakes Using The ResNet50 Algorithm Designed Through Deep Learning. It Analyzes Anomalies In Artificial Facial Images. Materials And Methods: The Two Implemented Deep Lear...
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...
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...
Multimodal Emotion Recognition Using Visual-Text Fusion With ResNet-50 And SVM On The MELD Dataset
This Paper Presents A Multimodal Emotion Recognition Framework That Integrates Visual And Textual Modalities To Improve The Accuracy And Robustness Of Emotion Classification Systems. The Visual Modality Is Processed Using A Pre-trained ResN...
Sign Language Classification Text And Voice Output System Using Resnet
Sign Language Is A Crucial Communication Medium For Individuals With Hearing And Speech Impairments. However, The Lack Of Widespread Accessibility To Sign Language Interpreter’s Limits Communication Opportunities For The Deaf And Mute Commu...
DEEP LEARNING CLASSIFICATION OF OPTICAL COHERENCE TOMOGRAPHY RETINAL IMAGES
This Study Presents A Deep Learning Approach For The Classification Of Optical Coherence Tomography (OCT) Retinal Images To Identify Various Retinal Diseases, Including Acrima, Cataract, Glaucoma, And Normal Retina, Utilizing The ResNet-50...
MELANOMA SKIN CANCER PREDICTION
Melanoma Cancer, Specifically Melanoma, Represents A Significant Public Health Concern Due To Its Potentially Aggressive Nature. Early Detection And Accurate Diagnosis Are Crucial In Improving Patient Outcomes. In Recent Years, Machine Lear...
IDENTIFYING PLANT DISEASE USING IMAGE PROCESSING AND DEEP LEARNING
In India's Economy, Agriculture Plays Important Role. To Prevent Crop Loss And Future Plants Disease Spread, Early Detection Of Plant Infections Is Extremely Important. The Majority Of Plants, Including Apple, Tomato, Cherry, And Grapes, Ex...
APPLYING RESIDUAL CONVOLUTIONAL NEURAL NETWORKS (RESNET) FOR AUTOMATED DETECTION OF LEUKAEMIA
The Present Work Proposes A Technique For Blood Cancer (leukemia) Classification Based On Machine Learning. Manual Classification Of Blood Cancer Is Very Challenging And Prone To Errors And Therefore Machine Learning Approaches Are Employed...
KIDNEY STONE DETECTION USING DEEP LEARNING
Kidney Stones Are A Common Complaint Worldwide, Causing Many People To Admit To Emergency Rooms With Severe Pain. Various Imaging Techniques Are Used For The Diagnosis Of Kidney Stone Disease. Specialists Are Needed For The Interpretation A...
SOFT BIOMETRIC TRAIT ON FINGERVEIN RECOGNITION USING CNNRESNET
Many Finger Vein Feature Extraction Algorithms Achieve Adequate Performance Due To Their Ability To Reflect Texture, While Simultaneously Ignoring The Finger Tissue-forming Intensity Distribution And In Some Cases Processing It As Backgroun...
AN IMPROVED DETECTION FRAMEWORK OF COVID-19 PATIENTS USING MACHINE LEARNING-BASED ENSEMBLE TECHNIQUES
COVID-19, A Novel Coronavirus, Is Currently Considered To Be A More Dangerous & Lethal Illness For The Human Body. In December 2019, The Coronavirus, Which Is Believed To Have Originated In Wuhan, China, Traveled Fast Over The Globe And Kil...
DEEP LEARNING APPROACHES TO DETECT COVID-19 USING CHEST X-RAYS
Novel Corona Virus Disease Called Covid-19 Is An Infectious Disease Caused By Newly Discovered Corona Virus, Which Causes The Difficulty In Breathing, Chest Pain And Loss Of Movements Or Speech. Approximately There Are 175 Million Confirmed...