Sökning: "embedded processing"

Visar resultat 1 - 5 av 199 uppsatser innehållade orden embedded processing.

1. 1. Image Quality Assessment Pipeline and Semi-Automated Annotation method for Synthetic Data

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Liam Le Tran; Edina Dedovic; [2023-10-24]
   Nyckelord :Facial Expression Recognition; FACS; Action Units; styleGAN2-ada; synthetic data; Image Quality Assessment; Multi-stage Pre-training; Pipeline Processing; Semi-automated Human Annotation;

   Sammanfattning : Predicting human emotions through facial expression, particularly in relation to medication field such as clinical trial settings, has garnered scientific interest in recent years due to significant understanding of the impact of treatment on emotions and social functioning. This thesis aims to improve performance of a FER model using large scale of synthetic data. LÄS MER

3. 2. Heart rate estimation from wrist-PPG signals in activity by deep learning methods

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Marie-Ange Stefanos; [2023]
   Nyckelord :Deep Learning; Medical Data; Signal Processing; Heart Rate Estimation; Wrist Photoplethysmography; Djup lärning; Medicinska Data; Signalbehandling; Pulsuppskattning; Handledsfotopletysmograf;

   Sammanfattning : In the context of health improving, the measurement of vital parameters such as heart rate (HR) can provide solutions for health monitoring, prevention and screening for certain chronic diseases. Among the different technologies for HR measuring, photoplethysmography (PPG) technique embedded in smart watches is the most commonly used in the field of consumer electronics since it is comfortable and does not require any user intervention. LÄS MER

4. 3. EMONAS : Evolutionary Multi-objective Neuron Architecture Search of Deep Neural Network

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Jiayi Feng; [2023]
   Nyckelord :DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Embedded Systems; DNN Deep Neural Network ; NAS Neural Architecture Search ; EA Evolutionary Algorithm ; Multi-Objective Optimization; Binary One Optimization; Inbyggda system;

   Sammanfattning : Customized Deep Neural Network (DNN) accelerators have been increasingly popular in various applications, from autonomous driving and natural language processing to healthcare and finance, etc. However, deploying them directly on embedded system peripherals within real-time operating systems (RTOS) is not easy due to the paradox of the complexity of DNNs and the simplicity of embedded system devices. LÄS MER

5. 4. Natural Language Processing on the Balance of theSwedish Software Industry and Higher VocationalEducation

   Kandidat-uppsats, Mittuniversitetet/Institutionen för kommunikation, kvalitetsteknik och informationssystem (2023-)

   Författare :Emil Bäckstrand; Rasmus Djupedal; [2023]
   Nyckelord :Swedish Software Industry; Higher Vocational Education; Software Engineering; Latent Dirichlet Allocation; Document Frequency Analysis;

   Sammanfattning : The Swedish software industry is fast-growing and in needof competent personnel, the education system is on the frontline of producing qualified graduates to meet the job marketdemand. Reports and studies show there exists a gapbetween industry needs and what is taught in highereducation, and that there is an undefined skills shortageleading to recruitment failures. LÄS MER

7. 5. RocksDB Read Optimization Strategies for Streaming Applications

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Björkman Fredrik; [2023]
   Nyckelord :RocksDB; Data streams; Micro-batching; Data stream processing; read operation benchmark; Data stream workload simulation; RocksDB; Dataströmmar; Mikro-batching; Dataströmsprocessering; Läsoperationsmätresultat; Dataströmsarbetsbelastningssimulation;

   Sammanfattning : Modern stream processors rely on embedded key-value stores to manage state that accumulates over long-running computations and exceeds the available memory size. One of these key-value stores is RocksDB, which is widely used in many applications requiring high-performing storage with low latency. LÄS MER