rspeer

psyyz10

This document summarizes some potentially useful papers and code repositories on Sentiment analysis / document classification

• CNN:

  1. Related Paper: Convolutional Neural Networks for Sentence Classification. EMNLP 2014

     A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification

     Code:

mbollmann

class AttentionLSTM(LSTM):
    """LSTM with attention mechanism

    This is an LSTM incorporating an attention mechanism into its hidden states.
    Currently, the context vector calculated from the attended vector is fed
    into the model's internal states, closely following the model by Xu et al.
    (2016, Sec. 3.1.2), using a soft attention model following
    Bahdanau et al. (2014).

    The layer expects two inputs instead of the usual one:

chsasank

require 'image'

function ElasticTransform(img, alpha, sigma)
	--[[
	Parameters
	----------
	img: Tensor of size KxHxW
		Image on which elastic transformation have to be applied
	alpha: number
		Intensity of the transformation

ViteFalcon

// create a camera to set up the projection and model view matrices, and the subgraph to draw in the HUD
osg::ref_ptr<osg::Camera> camera = new osg::Camera();

// set the view matrix
camera->setReferenceFrame(osg::Camera::ABSOLUTE_RF);
// use identity view matrix so that children do not get (view) transformed
camera->setViewMatrix(osg::Matrix::identity());
// set the projection matrix to be of width and height of 1
camera->setProjectionMatrix(osg::Matrix::ortho2D(0, 1.0f, 0, 1.0f));
// set resize policy to fixed

fmder

import numpy
from scipy.ndimage.interpolation import map_coordinates
from scipy.ndimage.filters import gaussian_filter

def elastic_transform(image, alpha, sigma, random_state=None):
    """Elastic deformation of images as described in [Simard2003]_.


    .. [Simard2003] Simard, Steinkraus and Platt, "Best Practices for
       Convolutional Neural Networks applied to Visual Document Analysis", in

thvasilo

import org.apache.spark._
import org.apache.spark.SparkContext._
import org.apache.spark.rdd.RDD
import scala.util.Random
import java.io._
import java.util.Properties

import org.apache.hadoop.fs._;
import org.apache.hadoop.conf._;
import org.apache.hadoop.io._;

thvasilo

#!/bin/bash

# Step 1: Install LZO dependencies
yum -y install lzo lzo-devel lzop

# Step 2: Install maven
MVN_VERSION=3.2.5
MVN_MD5=b2d88f02bd3a08a9df1f0b0126ebd8dc
# wget http://www.apache.org/dyn/closer.cgi/maven/maven-3/$MVN_VERSION/binaries/apache-maven-$MVN_VERSION-bin.tar.gz
wget http://apache.claz.org/maven/maven-3/$MVN_VERSION/binaries/apache-maven-$MVN_VERSION-bin.tar.gz

pklaus

#undef HID_ENABLED

// Arduino Due ADC->DMA->USB 1MSPS
// by stimmer
// from http://forum.arduino.cc/index.php?topic=137635.msg1136315#msg1136315
// Input: Analog in A0
// Output: Raw stream of uint16_t in range 0-4095 on Native USB Serial/ACM

// on linux, to stop the OS cooking your data: 
// stty -F /dev/ttyACM0 raw -iexten -echo -echoe -echok -echoctl -echoke -onlcr

jayrambhia

#include <errno.h>
#include <fcntl.h>
#include <linux/videodev2.h>
#include <stdint.h>
#include <stdio.h>
#include <string.h>
#include <sys/ioctl.h>
#include <sys/mman.h>
#include <unistd.h>
#include <opencv2/core/core.hpp>