Sökning: "Nätverk beskärning"
Visar resultat 1 - 5 av 6 uppsatser innehållade orden Nätverk beskärning.
1. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. LÄS MER
2. The impact of pruning Convolutional Neural Networks when classifying skin cancer
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Over the past few years, there have been multiple reports showcasing how Convolutional Neural Networks (CNNs) can be used to classify if skin lesions are cancerous or non-cancerous. However, a limitation of CNNs is the large number of parameters resulting in high computation times. LÄS MER
3. Pruning a Single-Shot Detector for Faster Inference : A Comparison of Two Pruning Approaches
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Modern state-of-the-art object detection models are based on convolutional neural networks and can be divided into single-shot detectors and two-stage detectors. Two-stage detectors exhibit impressive detection performance but their complex pipelines make them slow. LÄS MER
4. A Study on Fault Tolerance of Image Sensor-based Object Detection in Indoor Navigation
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : With the fast development of embedded deep-learning computing systems, applications powered by deep learning are moving from the cloud to the edge. When deploying NN onto the devices under complex environments, there are various types of possible faults: soft errors caused by cosmic radiation and radioactive impurities, voltage instability, aging, temperature variations, etc. LÄS MER
5. Optimizing web camera based eye tracking system : An investigating of the effect of network pruning and image resolution
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Deep learning has opened new doors to things that were only imaginable before. When it comes to eye tracking, the advances in deep learning have made it possible to predict gaze using the integrated camera that most mobile and desktop devices have nowadays. LÄS MER
