kaledhoshme123 / human-protein-atlas-image-classification

Proposing a neural network architecture capable of classifying protein organelle localization labels, the proposed model was able to reach an accuracy of 95 percent for test data and training data. The proposed model deals with the input of the proposed neural network as three-dimensional (each dimension represents colors (red filter, blue filter, yellow filter, green filter)), and thus the input to the neural network (samples, 2, 90, 90, 3) represents the number 2 In the proposed structure (RGB image, image with yellow filter).

Hi there 👋

• My name is Khaled. I graduated from Al-Baath University, Department of Computer Science. I have a passion for working in the field of computer vision and deep learning. I am interested in the field of image analysis using artificial intelligence. I focus on neural generative models in the ability to extract basic features from images and create new images with certain conditions and specifications.
• also interested in the field of generative arts (generating facial images with specific specifications, generating 3D images).
• I am working to increase my experience by reading many scientific books and studying two research papers every week in the field of computer vision, especially generative models.
• In addition to the interest in the field of analysis and detection of movement and early detection of future movement.

Certifications:

• Bachelor's degree in Computer Science from Al-Baath University - Syria.
• Probabilistic Deep Learning with TensorFlow 2 Course From Imperial College London: Certificate link
• AI for Medical Diagnosis by DeepLearning.AI Certificate link
• AI for Medical Prognosis by DeepLearning.AI Certificate link
• Advanced Computer Vision with TensorFlow by DeepLearning.AI Certificate link
• Advanced Deep Learning Methods for Healthcare by University of Illinois Certificate link