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John D. Pope's Projects

advance icon advance

A powerful animation framework for iOS, tvOS, and OS X.

advanced-lane-finding icon advanced-lane-finding

Udacity Self-Driving Car Engineer Nanodegree Advanced Lane Finding Project. Identifying lanes using edge detection (Sober operator, gradient of magnitude and direction, and HLS color space), camera calibration and unwarping (distortion correction and perspective transform), and polynomial fitting for the lanes.

adversarialaudioseparation icon adversarialaudioseparation

Code accompanying the paper "Semi-supervised adversarial audio source separation applied to singing voice extraction"

adversedrive icon adversedrive

Attacking Vision based Perception in End-to-end Autonomous Driving Models

adverts icon adverts

Adverts project using Vuejs, Design - Vuetify, DB - Firebase

adwords-query-ranking-oracle icon adwords-query-ranking-oracle

On-line advertising has been one of the most booming markets since the first on-line ads showed up on the web and now it is a market of hundreds of billions of dollars globally and it still has not lost the steam. Google got $32.2 billion in advertising revenue which is 97% of Google’s total revenue in Q3 2010 - Q2 2011. By far the most lucrative venue for on-line advertising has been search, and much of the effectiveness of search advertising comes from the “AdWords” model of matching search queries to advertisements. For this project, you need to use Java to access an Oracle database and accomplish an on-line ads auction system using various bidding algorithms. 1.1.1 Definition of the AdWords Problem We are going to consider on-line algorithms for solving the AdWords problem, which is defined as follows. Given: • A set of bids by advertisers for search queries; • A click-through rate for each advertiser-query pair; • A budget for each advertiser; • A limit on the number of ads to be displayed with each search query. Respond to each search query with a set of advertisers such that: • The size of the set is no larger than the limit on the number of ads per query. • Each advertiser has bid on the search query. • Each advertiser has enough budget left to pay for the ad if it is clicked upon. The data set consists of three database tables: (primary keys are underlined) Queries(qid:INTEGER, query:VARCHAR(100)) Advertisers(advertiserId:INTEGER, budget:FLOAT, ctc:FLOAT) Keywords(advertiserId:INTEGER, keyword:VARCHAR(100), bid:FLOAT)

aeparser icon aeparser

Convert After Effects tracking points to JSON

aepmultirender icon aepmultirender

バックグラウンドで複数のaerender.exeを起動させるもの

aerender icon aerender

Python asyncio wrapper for Adobe After Effects' aerender

aerial icon aerial

Aerial Apple TV screen saver for Windows

aetherdb-ios icon aetherdb-ios

iOS app using SwiftUI for accessing Aetheria database contents on RethinkDB

aetros-cli icon aetros-cli

AETROS SDK. Python library to manage/monitor deep neural network training in AETROS Trainer

aewriter icon aewriter

(Eyebeam #2 of 13) Record realtime procedural keyframe data, output a JS script for After Effects or a Python script for Maya.

aewriterjs icon aewriterjs

Web version of AEwriter, created for Tribeca Hacks at GAFFTA in 2013. Generate procedural keyframe data using Processing.js, output a JS script for After Effects or a Python script for Maya. Development continues at:

afharchiver icon afharchiver

An AFNetworking extension to automatically generate HTTP Archive files of all of your network requests!

afilm icon afilm

MLSP 2021 Self-Attention for Audio Super-resolution - Keras implementation

afl icon afl

Implementation of "Robust offline handwritten character recognition through exploring writer-independent features under the guidance of printed data" (AFL)

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