Join Esri in an AI Deep Learning Maritime seminar on Artificial Intelligence and Deep Learning in ArcGIS. This webinar covers how to use and automate machine-based object detection using convolutional neural networks in ArcGIS to solve real-world problems.
You can view the presentation slides here: https://bit.ly/3dJ5w46
Some additional materials from our Q&A session from the webinar, answered by our presenters, Madhu Hosuru and David Yu:
Q1: When you say collect ''as many as possible'' for training data, are you suggesting many analysts collect from the same data set? what are or do you suggest, and on what does your answer depend?
Q2: Any suggestions on how to collect training data, e.g. meaning as collect 'as many as possible'.
Q3: The presentation has only shown Geo AI against static features. How can GeoAI be applied to temporal and objects that change or move, such as cargo ships or determining tidal ranges.
Q4: Are the output(s) confidence/validity a function of the raster data resolution. That is low resolution low confidence/accuracy of results. Higher resolution higher confidence/accuracy of results.
Q5: Is arcgis a python library
Q6: Could this be applied to Multibeam Backscatter image classification? Extraction of seabed features, how successful would this be on greyscale imagery?
Q7: Can we request Esri's professional service for other country such as Asia instead Regional Distributor ?
Q8: Can GeoAI Deep Learning apply for "Digital Elevation Model" and "Digital Surface Model" or some other GIS model?
Q9: Is it possible to detect traffic volume using this technique?
Q10: How can false positive results after QA be fed back into the model to improve it?
Q11: can u provide ppt of this session?
Q12: Can the tool (or another in conjunction with it) extract dimensional attributes of the detected targets e.g. length, width, height?
Q13: How Geo AI recognize wrecks from Obstructions and underwater rocks?
Q14: Is it necessary to create a buffer around your training samples?
Q15: I have a question about Jupyter. Does it use GPU automatically for training the model? (Assuming that using GPU is the best equiped for training)
Q16: In what part of training your model the model creates buffers around your training data?
Q17: What licensing options are required, and are the deep learning tools available in Pro versions before 2.6?
Q18: How much training data i.e.
Q19: Do you provide any pre-trained models for fine-tuning?
Q20: Is it possible to subsequently execute this model on newly acquired imagery?
Q21: Will the shown Jupyter notebook be available?
Q22: Is there a reason this example is done in Jupyter instead of ArcGIS notebooks?
Q23: Can AI reliably detect gradients from imagery, instead of objects?
Q24: Does the training data include the bag layer or just the aspect?
Q25: Which wreck position is taken to S57, and which depth value is selected