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Visar resultat 1 - 5 av 28 uppsatser som matchar ovanstående sökkriterier.

1. 1. 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

3. 2. Exploring the aesthetical qualities of scaled game maps through Human-AI Collaboration

   M1-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)

   Författare :Petter Rignell; Christian Sjösvärd; [2023]
   Nyckelord :game design; scale; scalability; aesthetics; AI; Human-AI Collaboration; MAP-Elites; EDD;

   Sammanfattning : The primary objective is to explore the scalability of two-dimensional game maps while preserving certain aesthetical qualities in scaled representations. By either upscaling or downscaling the maps, features of the map inducing these aesthetical qualities may diminish. LÄS MER

4. 3. Automated Image Pre-Processing for Optimized Text Extraction Using Reinforcement Learning and Genetic Algorithms

   Kandidat-uppsats,

   Författare :Rahmat Rohoullah; Månsson Joakim; [2023]
   Nyckelord :BRISK; YOLO; Reinforcement learning; Evolutionary algorithm; OCR; Image pre-processing; Computer vision; BRISK; YOLO; Förstärkningslärning; Evolutionär algorithm; OCR; Bildförbehandling; Datorseende;

   Sammanfattning : This project aims to develop an automated image pre-processing chain to extract valuable information from appliance labels before recycling. The primary goal is to improve optical character recognition accuracy by addressing noise issues using reinforcement learning and an evolutionary algorithm. LÄS MER

5. 4. Benchmarking a memetic algorithm for global all-atom protein-protein docking with backbone flexibility

   Kandidat-uppsats, Lunds universitet/Kemiska institutionen

   Författare :Vera Karlin; [2022]
   Nyckelord :biochemistry; EvoDOCK; algorithm; protein; iRMSD; DockQ; CAPRI; Chemistry;

   Sammanfattning : Determining how proteins interact with each other to form complexes is very important for understanding both disease and cellular functions, but experimentally determining the structures of these complexes is both tedious and slow, which is why a great number of protein-protein docking algorithms have been developed to predict them. To this day, conformational changes in protein backbones have been one of the largest challenges when making docking predictions. LÄS MER

7. 5. Reinforcement learning for train dispatching : A study on the possibility to use reinforcement learning to optimize train ordering and minimize train delays in disrupted situations, inside the r ail simulator OSRD

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

   Författare :Teodora Popescu; [2022]
   Nyckelord :;

   Sammanfattning : Train dispatching is a complex process, especially when the train traffic is disrupted, as the decisions taken by the dispatchers can have substantial consequences on the delays of the trains. The most frequent dispatching decisions consists in changing the order of trains at convergence points, where two tracks unite to become a single track. LÄS MER