Sökning: "Resource-constrained devices"

Visar resultat 1 - 5 av 57 uppsatser innehållade orden Resource-constrained devices.

1. 1. The Impact of Deep Neural Network Pruning on the Hyperparameter Performance Space: An Empirical Study

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

   Författare :Jonna Matthiesen; [2023-10-24]
   Nyckelord :Compression; Deep Learning; DNN; Hyperparameters; Optimization; Pruning; Hyperparameter Optimisation; Hyperparameter Tuning;

   Sammanfattning : With the continued growth of deep learning models in terms of size and computational requirements, the need for efficient models for deployment on resource-constrained devices becomes crucial. Structured pruning has emerged as a proven method to speed up models and reduce computational requirements. LÄS MER

3. 2. Towards Adaptive Image Resolution for Visual SLAM on Resource-constrained Devices

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

   Författare :Herman Blenneros; [2023]
   Nyckelord :Visual localization and mapping; Runtime-control; Resource-constrained devices; Bildbaserad lokalisering och kartläggning; Realtidsreglering; Resursbegränsade enheter;

   Sammanfattning : Today, a large number of devices with small form factors and limited resources are being integrated with processes to perform complex tasks such as localization and mapping. One example of this are headsets used for Extended Reality. LÄS MER

4. 3. Evaluating Thread network performance, locating and strengthening weak radio links

   Master-uppsats, Linköpings universitet/Fysik, elektroteknik och matematik; Linköpings universitet/Tekniska fakulteten

   Författare :André du Rietz; Elias Salo; [2023]
   Nyckelord :Internet of Things; IoT; Thread network; Evaluating Thread Network;

   Sammanfattning : In the fast-developing world we are living in, a tech phenomenon known as the Internet of Things (IoT) has taken hold. It has seen a lot of development over the past few decades, and today there are an estimated 30 billion IoT devices active. IoT is a machine-to-machine network that senses the world with the help of sensors. LÄS MER

5. 4. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

   Master-uppsats, KTH/Mekatronik och inbyggda styrsystem

   Författare :Helgi Hrafn Björnsson; Jón Kaldal; [2023]
   Nyckelord :Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

   Sammanfattning : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. LÄS MER

7. 5. Anomaly Detection for Network Traffic in a Resource Constrained Environment

   Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

   Författare :Pontus Lidholm; Gaia Ingletto; [2023]
   Nyckelord :Network Traffic; Anomaly Detection; Embedded Systems; Machine Learning; Random Forest;

   Sammanfattning : Networks connected to the internet are under a constant threat of attacks. To protect against such threats, new techniques utilising already connected hardware have in this thesis been proven to be a viable solution. LÄS MER