| public class ArvoreBinaria { | |
| private No raiz; | |
| private ArvoreBinaria arvoreEsquerda; | |
| private ArvoreBinaria arvoreDireita; | |
| public ArvoreBinaria() { } | |
| public ArvoreBinaria getArvoreDireita() { | |
| return arvoreDireita; | |
| } |
| admin account info" filetype:log | |
| !Host=*.* intext:enc_UserPassword=* ext:pcf | |
| "# -FrontPage-" ext:pwd inurl:(service | authors | administrators | users) "# -FrontPage-" inurl:service.pwd | |
| "AutoCreate=TRUE password=*" | |
| "http://*:*@www” domainname | |
| "index of/" "ws_ftp.ini" "parent directory" | |
| "liveice configuration file" ext:cfg -site:sourceforge.net | |
| "parent directory" +proftpdpasswd | |
| Duclassified" -site:duware.com "DUware All Rights reserved" | |
| duclassmate" -site:duware.com |
This is the Keras model of VGG-Face.
It has been obtained through the following method:
Details about the network architecture can be found in the following paper:
Convolutional neural networks for emotion classification from facial images as described in the following work:
Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015
Project page: http://www.openu.ac.il/home/hassner/projects/cnn_emotions/
If you find our models useful, please add suitable reference to our paper in your work.
What follows is a technical test for this job offer at CARTO: https://boards.greenhouse.io/cartodb/jobs/705852#.WSvORxOGPUI
Build the following and make it run as fast as you possibly can using Python 3 (vanilla). The faster it runs, the more you will impress us!
Your code should:
| from nltk.tokenize import word_tokenize | |
| import pickle | |
| import pprint | |
| import json | |
| """ | |
| (heads, descs, keywords) = ([headline], [description], ) | |
| """ |
| git rm -r --cached node_modules | |
| git commit -m 'Remove the now ignored directory node_modules' | |
| git push origin master |
| /* globals localStorage */ | |
| import { onSnapshot, applySnapshot } from 'mobx-state-tree'; | |
| import Storage from './storage'; | |
| export const persist = (name, store, options, schema = {}) => { | |
| let hydrated = false; | |
| let storage = options.storage; | |
| if (typeof localStorage !== 'undefined' && localStorage === storage) { |
| /** | |
| * Basic CSS Media Query Template | |
| * TODO: I should probably use Sass... | |
| * Author: Michael Vieth | |
| * ------------------------------------------ | |
| * Responsive Grid Media Queries - 1280, 1024, 768, 480 | |
| * 1280-1024 - desktop (default grid) | |
| * 1024-768 - tablet landscape | |
| * 768-480 - tablet | |
| * 480-less - phone landscape & smaller |
| <html> | |
| <head> | |
| <script src="/javascripts/CryptoJS/rollups/aes.js"></script> | |
| <script src="/javascripts/CryptoJS/components/mode-cfb-min.js"></script> | |
| <script src="/javascripts/encrypt.js"></script> | |
| </head> | |
| <body> | |
| </body> | |
| </html> |