Image Recognition Using Convolutional Neural Networks
Table Of Contents
<p>1. Introduction to Convolutional Neural Networks<br>2. Convolutional Layers and Feature Extraction<br>3. Pooling and Striding in CNNs<br>4. Training CNNs: Backpropagation and Optimization<br>5. Transfer Learning and Fine-tuning<br></p>
Thesis Abstract
<p> This project focuses on developing image recognition systems using convolutional neural networks (CNNs). CNNs have demonstrated remarkable performance in tasks such as object detection, image classification, and facial recognition. The project will explore the architecture of CNNs, training methodologies, and transfer learning techniques for image recognition. Additionally, the project will address challenges related to data augmentation, model interpretability, and real-world deployment of CNN-based image recognition systems. <br></p>Thesis Overview
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