Bachelorprosject, group 20

A bachelor project that entails object detection for road- and transportation related image data. Written for the company Triona

Object Detection

Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. Well-researched domains of object detection include face detection and pedestrian detection.

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Machine Learning

Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to progressively improve their performance on a specific task. Machine learning algorithms build a mathematical model of sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task.

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Infrastructure

Infrastructure refers to the fundamental facilities and systems serving a country, city, or other area, including the services and facilities necessary for its economy to function. Infrastructure is composed of public and private physical improvements such as roads, bridges, tunnels, water supply, sewers, electrical grids, and telecommunications (including Internet connectivity and broadband speeds).

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Triona

Triona is a leading and reliable supplier of innovative IT solutions within logistics- and infrastructure-oriented operations. They combine industry-specific competence and skills in transport infrastructure, power/energy, contractor related businesses, transports and forest industry with leading-edge experience within software engineering and maintenance.

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Group members

The group consists of three students from OsloMet who all study Applied Computer Science.

Lukas Haug Langøy

Group Leader


Isak Kvalvaag Torgersen

Coordinator


Pål Magnus Østern

Spokesman


Status rapport

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Prosject outline

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Forprosjekt

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Sluttprosjektrapport

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