A5093820750- COVID-19 diagnosis using AI
- Brain Tumor Detection and Classification
- IoT and Edge/Fog Computing
- Security in Wireless Sensor Networks
- Advanced Neural Network Applications
- Chaos-based Image/Signal Encryption
- Colorectal Cancer Screening and Detection
- Artificial Intelligence in Healthcare
- IoT-based Smart Home Systems
- Image Retrieval and Classification Techniques
- AI in cancer detection
- Advanced Malware Detection Techniques
- Medical Research and Treatments
- Retinal Imaging and Analysis
- Imbalanced Data Classification Techniques
- Smart Systems and Machine Learning
- Energy Efficient Wireless Sensor Networks
- Molecular Communication and Nanonetworks
- Quantum Computing Algorithms and Architecture
- Financial Distress and Bankruptcy Prediction
- Cloud Data Security Solutions
- Explainable Artificial Intelligence (XAI)
- Advanced Optical Network Technologies
- Generative Adversarial Networks and Image Synthesis
- Advanced Chemical Sensor Technologies
Aeronautical Development Agency
2024
In the digital era, authentication system’s security is crucial. This paper discusses issue of improving from position cryptographic improvements in intrinsic verification structures. The emphasis made on creation and implementation efficient protocols that reinforce procedures. research focuses developing a new framework capable attack tolerance systems against various kinds cyber-attacks such as identity theft data breach. structure takes advantage innovative algorithms, including...
There is need to develop and create new data protection mechanisms aimed at the compensating for lack of security WSNs. This paper introduces cryptographic image-based techniques improving in The solution also integrates imaging processing with advanced principles merge a two-layered architecture. work provides WSN-specific encryption algorithm that delivers low energy consumption smaller computational burden. Likewise, this connected an authentication approach which employs steganographic...
The abstract highlights the critical need for securing sensitive medical data, emphasizing challenges in domain due to confidentiality of patient, disease, doctor, and staff information. proposed study introduces a novel approach using machine learning, specifically integrating firefly optimization technique with random forest algorithm, classify data secure manner. significance lies addressing security concerns associated datasets, offering solution that prioritizes throughout software...
TumorDiagX is a cutting‐edge framework that combines deep learning and computer vision to accurately identify classify cancers. Our collection of colonoscopies 1518 images meticulously pre‐processed, including greyscale conversion local binary pattern (LBP) extraction, before being securely stored on the Google Cloud platform. In second phase, we fully assess three different convolutional neural networks (CNNs): residual network with 50 layers (ResNet‐50), DenseNet‐201 visual geometry group...
Digital mammography increasingly necessitates image segmentation for the purpose of dividing mammograms into individual slices. For removing suspicious masses or tumours from mammograms, this process is carried out using a region interest (ROI). More training photos are needed classification, and these circumstances, ROI requires more processing time. The temporal complexity difficulties with suggested multi-ROI method subject article. To show how effective compared to current approach,...
Social media has become a part of our lives with countless individuals actively sharing content and connecting others. However this open platform also presents challenge, in dealing misinfor- mation the spread information by individuals. platforms face task identifying these users preventing dissemination content. In study focus is on Twitter as case example. Explore use deep learning techniques to detect fake accounts. We analyze factors such account age, follower following ratio, tweet...
In the realm of disaster response, integration Internet Things (IoT) technologies has paved way for innovative solutions to enhance human detection and rescue operations. This research work introduces a revolutionary approach through development Challenging Human Detection Rescue Robot (CHDRR). robot incorporates advanced sensors, including MQ6 Gas Sensor, LM335 Temperature Humidity Passive Infrared (PIR) Body sensor, collectively forming comprehensive sensory suite. The CHDRR leverages...