Trapped Ion Quantum Computers - Platform for QNN Neuroradiology
Explore trapped ion quantum computers' potential in neuroradiology through analysis of key papers on fault-tolerant circuits, quantum CNNs, and image classification for ischemic cardiopathy.
MRI Brain Scan Classification Using FastSurfer, XGBoost and 3D CNNs
Master medical image classification techniques using FastSurfer pipeline, XGBoost, and 3D CNNs for MRI brain scan analysis. Learn preprocessing steps and implement neural networks in PyTorch for advanced medical data analysis.
Identifying Subgroups in Biomedical Datasets Using Data Attribution
Explore data attribution methods for machine learning models, focusing on identifying disease subtypes and meaningful patterns in biomedical datasets through hands-on practice with datamodels.
Leaf Tracking, Counting and Occlusion in Plants Using Artificial Neural Networks
Discover how to implement artificial neural networks for plant leaf analysis, including tracking, counting, and handling occlusion through advanced image processing techniques.
Introduction to Neural Networks
Explore neural networks, their components, and architectures. Learn about RNNs, LSTMs, and CNNs with practical examples in Python for movie review and image classification tasks.
Vision Transformer - Lecture 14
Explore Vision Transformers in deep learning, covering architecture, training, and applications. Gain insights into this powerful model for computer vision tasks.
Vision Transformer - Lecture 14
Explore Vision Transformers in deep learning, covering architecture, training, and applications. Gain insights into this powerful model for computer vision tasks.
Developing New Quantum Neural Networks for Neuroradiology
Explore quantum neural networks for neuroradiology, focusing on modifications to Qiskit/Python circuits, updated fit times, fidelity values, and applications in MRI/PET image classification.
Quantum-Classical Hybrid Code for Neuroradiology Algorithms - Demo
Explore quantum-classical hybrid systems for neuroradiology, focusing on potential advancements in data processing, kernel sizes, and qubit entanglement for improved medical image analysis.
Adversarial Machine Learning: Beyond Manipulating Pixels and Words
Explore vulnerabilities in sequential machine learning and challenge assumptions about imperceptible attacks on image classification through human behavioral studies.
The Perceptron as a Roadmap - From Neuron Structure to Artificial Neural Networks
Explore the evolution of neural networks from biological neurons to machine learning, using the perceptron as a guide. Uncover connections to associative memories, function approximation, and surprising mathematical links.
Learn OpenCV in Python - Computer Vision Projects
Comprehensive Python-based OpenCV tutorial covering fundamentals to advanced applications, including face detection, object tracking, and image classification. Ideal for aspiring computer vision professionals.
Building a Visual Inspection System for Defect Detection with Python
Learn to create a Python-based visual inspection system that automatically detects and identifies surface defects using AI and computer vision techniques.
Abstraction and Evolution with Large Language Models
Explore how large language models enhance genetic programming through concept-guided evolution, with applications in symbolic regression and image classification demonstrated through practical examples.
Decentralized Federated Machine Learning: Empowering Edge Devices with Kubernetes
Discover how to implement Federated Machine Learning with Kubernetes for privacy-preserving model training across edge devices, enabling efficient image classification and scaled computations.