Sökning: "Embedded computer"
Visar resultat 21 - 25 av 209 uppsatser innehållade orden Embedded computer.
21. 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
22. AntiKli-MAX 5000 : A robotic head massager with an implemented distance sensor
Magister-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : Robots are increasingly being used in personal households for service-related tasks such as floor cleaning, lawn mowing or entertainment. However, there is still a lack of household robots performing tactile service-related tasks that requires human-robot interaction. LÄS MER
23. A Benchmark and Evaluation of Imperas OVPSim Virtual Platform Tool Using RISC-V Processors
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In recent years, there has been a rapid development of embedded processors. These processors are designed for domains like aerospace, automotive, automation, healthcare, and more. However, both hardware and software must be validated before the actual application. Manufacturing a processor requires extremely high cost and a long time to finish. LÄS MER
24. Hybrid Debugger Software on RISC-V MCU : A no cost debugging solution foreducational use
Kandidat-uppsats, KTH/Hälsoinformatik och logistikSammanfattning : This work details the implementation of a debugger for a small embedded RISC-V system. KTH uses an in-house designed microcontroller development board for computer and electronics design courses. LÄS MER
25. Mapping quantized convolutional layers on the SiLago platform
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Convolutional neural networks (CNNs) have been utilized in various applications, such as image classification, computer vision, etc. With development, the complexity and computation of CNNs also increase, which requires more memory and resources when deployed on devices, especially embedded systems. LÄS MER