implemented a steganography detection system using the SRNet (Spatial Rich Model Network) deep learning architecture
The model was trained on the ALASKA2 dataset to detect hidden information embedded in digital images
The system leverages convolutional neural networks (CNNs) to accurately identify subtle changes in image structures caused by steganographic methods
This project demonstrates my skills in computer vision, deep learning, and information security, as well as my proficiency with frameworks such as TensorFlow for model development and training
