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Papers tagged with "Sar"
Detecting AI-Generated Content: A Survey On Multimodal Detection Of Text, Image, And Video
Generative AI Has Advanced Very Quickly Allowing The Generation Of Realistic Fake Content In Text, Image, And Video Domains That Is Becoming Challenging To Differentiate From Real Content. While There Has Been Some Progress In Developing De...
ROLE OF BRAND AWARENESS AND BRAND LOYALTY TOWARDS CONSUMER BUYING BEHAVIOUR IN LIC SARAVANAMPATTI COIMBATORE
This Study Examines The Impact Of Brand Awareness And Brand Loyalty On Consumer Buying Behaviour With Specific Reference To Life Insurance Corporation (LIC) In Saravanampatti, Coimbatore. It Aims To Understand How Familiarity With The LIC B...
A Non-Hierarchical AI Framework For Secure Blockchain Anomaly Detection
Blockchain Technology Has Changed The Way Of Conducting Business By Providing A New Form Of Organization That Is Decentralized, Secure And Transparent. Nevertheless, Having Gained Popularity, It Has Become A Major Hub For Adversarial Attack...
A Blue Tea California in the treatment of varies disease
Synthetic Aperture Radar (SAR) Image Colorization Using Deep Learning Aims To Convert Grayscale Radar Images Into Visually Meaningful Color Representations. By Leveraging Models Like U-Net And GANs, This Process Combines SAR Data, Such As P...
Leveraging gan for synthetic medical image synthesis
Generative Adversarial Networks (GANs) Generate Realistic Medical Images, Tackling The Scarcity Of Annotated Datasets In Healthcare. Models Like Conditional GANs And CycleGANs Preserve Essential Clinical Features, Improve Model Generaliza...
SAR IMAGE COLOURIZATION FOR COMPREHENSIVE INSIGHT USING DEEP LEARNING
Synthetic Aperture Radar (SAR) Image Colorization Using Deep Learning Aims To Convert Grayscale Radar Images Into Visually Meaningful Color Representations. By Leveraging Models Like U-Net And GANs, This Process Combines SAR Data, Such As P...
A SCRUTINY ON ANTI-COVID ACTIVITY OF HETEROCYCLIC COMPOUNDS
The Coronavirus Disease 2019 (COVID-19) Pandemic Is One Of The Most Serious Health Problems Worldwide. It Has Caused Serious Calamities In The World Since The Blaze Of SARS CoV In 2002 And Then MERS CoV In 2012.The Pandemic Caused By SARS C...
Early Detection of Network Intrusions, One-Class Classifier
Early Detection Of Network Intrusions Is A Very Important Factor In Network Security. However, Most Studies Of Network Intrusion Detection Systems Utilize Features For Full Sessions, Making It Difficult To Detect Intrusions Before A Session...
A NOVEL DEEP LEARNING METHOD FOR MARINE OIL SPILL DETECTION FROM SATELLITE SYNTHETIC APERTURE RADAR IMAGERY
Oil Spill Detection Is Essential For Keeping The Maritime Ecology In Good Condition. The Use Of Quad-polarimetric Synthetic Aperture Radar (SAR) Has Demonstrated To Be Highly Promising In This Regard. It Is Advantageous To Distinguish Oil S...
PERSON RE IDENTIFICATION USING CONVOLUTIONAL NEURAL NETWORK
Deep Learning Is A Subset Of Machine Learning, Which Is Essentially A Three-layer Neural Network. These Neural Networks Try To Mimic The Behaviour Of The Human Brain, But They Are Far From Being Able To "learn" From Large Amounts Of Data. T...
Generative AI: Impact on Software Engineering & Ethical Considerations
Generative Artificial Intelligence (Generative AI) Has Become A Groundbreaking Technology In Recent Years, Showcasing Significant Advancements. This Research Paper Delves Into The Progress Achieved In Generative AI, Its Impact On Software E...
GENERATIVE AI: ADVANCEMENTS, APPLICATIONS AND ETHICAL CONSIDERATIONS
Generative Artificial Intelligence (Generative AI) Has Emerged As A Transformative Technology With Significant Advancements In Recent Years. This Research Paper Explores The Progress Made In Generative AI, Its Diverse Applications Across Va...
GENERATIVE AI
Generative Artificial Intelligence (Generative AI) Stands At The Forefront Of Innovation, Revolutionizing Data Generation And Creative Content Production. This Paper Explores The Multifaceted World Of Generative AI, Delving Into Its Diverse...
REDUCING FREQUENT KILLING OF ELEPHANTS FROM TRAIN COLLISION USING MACHINE LEARNING
Elephant Train Collisions Are A Significant Concern In Wildlife Conservation And Transportation Safety, As They Can Lead To Loss Of Human Life, Financial Losses, And Endangerment Of Elephant Populations. To Mitigate This Risk, Machine Learn...
GENERATIVE ADVERSARIAL NETWORKS : A REVIEW
GANs Have Gained Much Attention From The Research Community In Recent Years In Terms Of Generating Quality Images And Data Augmentation. Generative Adversarial Networks (GANs) Present A Way To Learn Deep Representations Without Extensively...