
Explore satellite and drone imagery analysis in data science workflows using RasterFrames, a Spark SQL extension with Python API for processing spatial image data and integrating with ML frameworks.

Explore topological data analysis for plant morphology using persistent homology and Euclidean Distance Transform. Learn applications in hurricane video data and XRay CT scans of plants.

Explore topological data analysis for detecting fake faces in images and videos. Learn about image landmarks, texture descriptors, and performance testing on passport photos and DeepFake videos.

Explore the impact of CNN layers on image topological texture features, examining their effectiveness in detecting subtle changes and understanding decision-making processes in image analysis.

Explore lower dimensional topological features in data analysis, covering detection methods, theoretical foundations, and applications in image segmentation using topological and statistical approaches.

Interactive exploration of TDA's key applications using Python, covering time series analysis, image processing, 3D shape clustering, and more. Hands-on examples showcase TDA's versatility and practical uses.

Exploring mathematical morphology through persistent homology, offering new insights for image processing and automated denoising techniques in binary, grayscale, and color images.

Learn to create and deploy a Python-based YouTube thumbnail downloader using Streamlit, from concept to live web application. Gain practical experience in building and hosting a useful tool for content creators.

Learn to create a deadlift bot using MediaPipe and OpenCV in this hands-on live stream, exploring practical applications of computer vision and machine learning for fitness tracking.

Explore robust PCA for handling corrupted data in fields like fluid mechanics and image processing. Learn its applications and importance in data-driven science and engineering.

Explore persistent homology in machine learning, covering applications in materials science, computer vision, and agent-based modeling. Learn how topology relates to dataset geometry and explainable AI.

Master image embeddings and vector analysis techniques like CLIP, T-SNE, and UMAP. Learn to cluster MNIST images, detect duplicates, and explore essential concepts in computer vision and data science through hands-on practice.

Explore datasets for intelligent XR applications in this IEEE VR 2022 workshop. Learn about AI-driven models, challenges in XR research, and opportunities for cross-lab collaborations.

Explore cutting-edge deep dictionary learning techniques for image super-resolution with Pier Luigi Dragotti from Imperial College, bridging mathematics and data science in this advanced workshop.

Explore how distributed Kubernetes clusters and AI revolutionize cancer diagnosis, combining computational biology with cloud computing for faster, more precise treatments.

Explore geometric graph-based methods for segmenting large datasets, combining nonlinear PDE image segmentation with linear algebra techniques to solve graph cut optimization problems in various applications.

Insightful panel discussion exploring deep learning advancements, industry applications, and future trends with experts from Huawei, China Mobile Research Institute, and The Linux Foundation.

Comprehensive overview of recent AI advancements, including new models, tools, and industry developments. Covers a wide range of topics from audio generation to LLM applications and ethical considerations.

Explore how visual technology is reshaping inspiration, idea discovery, and personal pursuits with Pinterest's CEO, discussing challenges, innovations, and the platform's unique approach.

Explore computer vision applications in real-world problem-solving through an interactive workshop from the Alan Turing Institute's Research in Action series.

Explore unconventional data transformations using Ruby, turning files into audio, images, and music. Learn byte manipulation techniques while discovering creative ways to represent information.