Sökning: "Video Traffic Classification"

Visar resultat 1 - 5 av 14 uppsatser innehållade orden Video Traffic Classification.

1. 1. Gunshot Detection from Audio Streams in Portable Devices

   Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

   Författare :Linnea Bokelund; Ellen Grane; [2022]
   Nyckelord :machine learning; gunshot detection; convolutional neural networks; sound event detection; portable devices; Technology and Engineering;

   Sammanfattning : Machine learning and artificial neural networks can be used to classify or detect specific sound events in audio signals. Gunshot detection is one use case for such networks and can be used to help law enforcement by alerting officers or triggering camera recordings. LÄS MER

3. 2. Video-Based Estimation of Driver Sleepiness Using Machine Learning

   Master-uppsats, Linköpings universitet/Institutionen för systemteknik

   Författare :Simon Knutsson; [2022]
   Nyckelord :Driver sleepiness; drowsiness; classification; estimation; machine learning;

   Sammanfattning : Approximately 1.35 million people die each year in car accidents and it is the most common cause of death for people aged 5-29. Because of this it is of large interest to be able to detect when a driver enters a sleepy state and to be able to alert the driver. LÄS MER

4. 3. Scene analysis using Tensorflow & YOLO algorithms on Raspberry pi 4

   Uppsats för yrkesexamina på grundnivå, Högskolan i Halmstad/Akademin för informationsteknologi

   Författare :Nivethan Marmayohan; Abdirahman Farah; [2021]
   Nyckelord :;

   Sammanfattning : Objektdetektion är en av de viktigaste mjukvarukomponenterna i nästa generation trafikövervakning. Deep learnings-algoritmer för objektdetektion, exempelvis YOLO (You Only Look Once), är snabba och noggranna algoritmer i realtid. Realtidsdetektion och igenkänning av objekt är viktiga uppgifter för bildbehandling. LÄS MER

5. 4. Identification of Flying Drones in Mobile Networks using Machine Learning

   Master-uppsats, Linköpings universitet/Kommunikationssystem

   Författare :Elias Alesand; [2019]
   Nyckelord :Drones; Machine Learning; LTE; Mobile networks; Radio; Decision tree; Ensemble learning;

   Sammanfattning : Drone usage is increasing, both in recreational use and in the industry. With it comes a number of problems to tackle. Primarily, there are certain areas in which flying drones pose a security threat, e.g. LÄS MER

7. 5. Terrain Classification to find Drivable Surfaces using Deep Neural Networks : Semantic segmentation for unstructured roads combined with the use of Gabor filters to determine drivable regions trained on a small dataset

   Master-uppsats, KTH/Robotik, perception och lärande, RPL

   Författare :Agneev Guin; [2018]
   Nyckelord :Semantic segmentation; Deep learning; Gabor filters; Drivable surfaces;

   Sammanfattning : Autonomous vehicles face various challenges under difficult terrain conditions such as marginally rural or back-country roads, due to the lack of lane information, road signs or traffic signals. In this thesis, we investigate a novel approach of using Deep Neural Networks (DNNs) to classify off-road surfaces into the types of terrains with the aim of supporting autonomous navigation in unstructured environments. LÄS MER