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AI in agriculture is only as good as the data behind it, but messy datasets, poor annotations, and hidden biases slow progress. Join Paula for a dynamic session on semantic segmentation, where she will show how FiftyOne can transform dataset curation, annotation analysis, and model evaluation for agricultural AI. Using real-world coffee datasets from Colombia, we’ll dive into the segmentation of coffee fruits at different maturation stages, leveraging FiftyOne’s powerful tools, from uniqueness detection to similarity search and embedding visualizations. Whether interested in farm robotics, remote sensing, or plant phenotyping, this talk will give you actionable techniques to refine your datasets and supercharge your AI workflows. #computervision #ai #artificialintelligence #machinevision #machinelearning #datascience #opensource Contents of this video -- 00:00 - Introduction 00:52 - Background and Mission in AI for Agriculture 01:48 - Importance of Coffee in Colombia 02:54 - Empowering Farmers with Mobile Tools 03:43 - Data Collection and Device Design 04:47 - Challenges in Coffee Yield Estimation 05:52 - Project Timeline and Annotation Process 07:05 - Computer Vision and 3D Analysis Techniques 08:01 - Revisiting Past Models with New Tools 08:34 - Introducing the Coffee Dataset with FiftyOne 09:22 - Using the FiftyOne App for Dataset Inspection 11:04 - Understanding Embeddings and Outliers 12:01 - Improving Dataset Quality with FiftyOne 13:33 - Data-Centric AI vs. Model-Centric AI 14:09 - Loading and Exploring Data with FiftyOne SDK 15:04 - Interactive Geolocation Plot for Agriculture 17:02 - Visualizing Regional Coffee Data 17:51 - Dataset Support and Use Cases in FiftyOne 18:31 - Using SAM-2 with FiftyOne’s Model Zoo 20:26 - Pre-Annotation Strategy with Unique Samples 22:01 - Annotation Integration and CAT Tool 23:36 - Training Model and Achieving 90% Accuracy 24:54 - Embracing a Data-Centric AI Approach 26:02 - Visual AI Benefits with FiftyOne 27:36 - Final Call to Action and Resources 28:13 - Audience Q&A: Unique vs. Large Datasets -- #computervision #ai #artificialintelligence #machinevision #machinelearning #datascience #opensource