class: center, middle, inverse, title-slide # Weekly Update for July 9 ### 2018/07/09 --- class: inverse # About Slides --- class: primary # New CSAFE slide template We're now using [`xaringan`](https://github.com/yihui/xaringan) What's changed: - New person slide: ```` --- class: inverse # Your Name ```` --- class: secondary - New content slide with title: ```` --- class: primary # Title of slide Slide content ```` - New content slide without title: ```` --- class: secondary Slide content with no title on slide ```` --- class: inverse # Sample User --- class: primary # Sample Slide - Sample Table: | Team | Probability | | : ------ | :---------- | | France | 29% | | England | 27% | | Belgium | 26% | | Croatia | 18% | --- class: secondary - If you are going to add an image, **create a directory** with your name within "images" folder. For example, "images/**guillermo**/sample_image.JPG" <img src = "images/guillermo/sample_image.JPG" width="35%"/> --- class:inverse # Miranda --- class:primary # Neural Networks - Most recent model (classifying circles vs. triangles) using VGG16 has **94.8% accuracy** on test set! - Next questions - Is VGG19 (more layers) better than VGG16? - Effect of different classes on accuracy? (e.g., quadrilateral, text) - How to handle multi-class images? - Binary encoding/classification for each shape - Multi-label neural network --- class: primary # Architecture - **Convolutional layers** learn local patterns by analyzing the image through a sliding window - **Max-Pooling layers** combine patterns learned in single windows, downsampling huge feature maps and creating feature hierarchies of importance <img src = "images/miranda/imagenet_vgg16.png" width="80%"/> --- class:primary # Visualizing Filters <img src = "images/miranda/aerosoles-pin-down-black-leather_product_9010211_color_72_crop2.png" width="70%"/> --- class:secondary 1st Convolutional Layer <img src = "images/miranda/activations/1_conv2d_17.png" width="80%"/> 2nd Convolutional Layer <img src = "images/miranda/activations/3_conv2d_18.png" width="80%"/> *A blank square means the filter's pattern is not found in the image --- class:secondary 3rd Convolutional Layer <img src = "images/miranda/activations/5_conv2d_19.png" width="80%"/> --- class:secondary 4th Convolutional Layer <img src = "images/miranda/activations/7_conv2d_20.png" width="80%"/> --- class: inverse # Jenny and Ben --- class: primary # Shoe tread classifications - 1645 classifications total --- class: primary # Realistic Print Experimental Setup  --- class: primary # Realistic Print Experimental Setup  --- class: inverse # Susan --- class: primary # Realistic Print Experimental Setup  --- class: primary # Realistic Print Experimental Setup  --- class:primary # Truthiness - 6 facts down, 6 more to go - 10 pictures/plots per fact - Formalized the experimental design It's surprisingly hard to find specific bits of data, such as the length of a border with a body of water. :-/ --- class: inverse # Kiegan --- class: primary # Sorry I can't be there! <img src = "images/kiegan/this-is-fine.0.jpg" width="50%"/> --- class: inverse # Martin --- class: primary # Brief update - Working on alignment of two different pattern shoeprints - Still struggling with the speed of processing the 4243x1645 pixels full size image - Currently working on doing the processing using RCpp - I also filtered and preprocessed some EverOS images from the database that Soyoung needs --- class: inverse # Sam --- class: primary # Summer activities thus far - REU https://csafe-isu.github.io/reu18/ - Judge/lawyer training for ABA annual meeting in Chicago in August - Working on submitting paper to JCGS before JSM --- class: inverse # Jimmy --- class: primary # Longitudinal Data Collection * Document Development + Detailed outline of all changes made during collection + Updates on all procedure manuals * Automated File development + Mat Scanner Files + These should be all remaining errors --- class: inverse # Nate --- class: primary # Bullet Changepoint - Changepoint analysis with Gibbs is currently running - Currently the samples is a two step, random walk Metropolis within Gibbs. - Preliminary results on next few slides --- class: secondary - Vertical lines show posterior means of the changepoints - So far, so good. <img src = "images/Nate/hamby1_cp.PNG" width="75%" height="75%"/> --- class: secondary - This is what happens when only one shoulder(?) is present. <img src = "images/Nate/hamby3_cp.PNG" width="75%" height="75%"/> --- class: secondary - The case when there is little data after a shoulder might be challenging. <img src = "images/Nate/hamby5_cp.PNG" width="75%" height="75%"/> --- class: secondary - This looks fine so far. Starting values are dashed lines. <img src = "images/Nate/hamby6_cp.PNG" width="75%" height="75%"/> --- class: secondary - When bad starting values are used. <img src = "images/Nate/hamby6_cp_bad_svals.PNG" width="75%" height="75%"/> --- class: secondary - When bad starting values are used but a high proposal variance is used. <img src = "images/Nate/hamby6_cp_bad_svals_high_var.PNG" width="75%" height="75%"/> --- class: inverse # Guillermo --- class: secondary - Automating extraction of data from MatScan files with AutoIt + Make different windows active + Need to come up with a way to move already processed files - Set the right name for every file with R - Fixing renamed vinyl pictures --- class: inverse # REU Students --- class: primary # Malisha Jones  - Goal: To Create The Best Possible Graph! :) --- class: primary # Yolonda - 10/54 documents completed - Problems with telling letters apart   Author 26, document 4 --- class: primary # Da'Monie Handwriting - Assigned a total of 54 documents from 9 different writers to classify handwritten letters. - In a week, I have completed 8/54 documents. Errors: - Can only select a "square" region. - Some letters overlap with the next letter in the word. <img src = "images/0002_1a.png"> --- class: primary # Alese Making models and graphs using mock jury survey data. <img src = "images/Age vs. Understood Evidence.png"> --- class: primary # Badiah - Jury project + Initial Verdict - Fitting different models - Changing ordinal data to numerical data --- class: primary # Carley - Taking images of letters to train computer to classify letters - Completed 12 out of 54 of my documents - Issues - Letters that look the same <img src = "images/Carley_letter n.png" width="25%" height="25%"/> n <img src = "images/Carley_letter a.png" width="25%" height="25%"/> a <img src = "images/Carley_letter u.png" width="25%" height="25%"/> u --- class: primary # Mark Lancaster Mind map regarding the evaluation of evidence  https://mm.tt/1119875312?t=Z5g2sHX4AO