Essays about: "Apprentissage Profond"

Found 3 essays containing the words Apprentissage Profond.

1. 1. Deep Reinforcement Learning on Social Environment Aware Navigation based on Maps

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Victor Sanchez; [2023]
   Keywords : Deep Reinforcement Learning; Environment-aware navigation; Robotics; Artificial Intelligence; Apprentissage par renforcement profond; Navigation consciente de l’humain; Intelligence Artificielle; Robotique; Djup Förstärkande Inlärning; Människomedveten navigering; Robotik; Artificiell Intelligens;

   Abstract : Reinforcement learning (RL) has seen a fast expansion in recent years of its successful application to a range of decision-making and complex control tasks. Moreover, deep learning offers RL the opportunity to enlarge its spectrum of complex fields. READ MORE

3. 2. Transformer-Based Multi-scale Technical Reports Analyser for Science Projects Cost Prediction

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Thomas Bouquet; [2023]
   Keywords : Natural Language Processing; Transformers; Deep Learning; Cost Prediction; Traitement Automatique du Langage; Transformers; Apprentissage Profond; Prédiction de coûts; Behandling av naturligt språk; Transformers; Djupinlärning; Kostnadsförutsägelser;

   Abstract : Intrinsic value prediction is a Natural Language Processing (NLP) problem consisting in determining a numerical value contained implicitly and non-trivially in a text. In this project, we introduce the SWORDSMAN model (Sentence and Word-level Oracle for Research Documents by Semantic Multi-scale ANalysis), a deep neural network architecture based on transformers whose goal is to predict the cost of research projects from the analysis of their abstract. READ MORE

4. 3. Hybrid Deep Learning Model for Cellular Network Traffic Prediction : Case Study using Telecom Time Series Data, Satellite Imagery, and Weather Data

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Ali Shibli; [2022]
   Keywords : Cellular network traffic; multi-modal; satellite imagery; weather data; LSTM; CNN; time series; Trafic sur les réseaux cellulaires; multimodal; imagerie satellite; données météo; LSTM; CNN; séries temporelles; Förutsägelse av mobilnätstrafik; multimodal modell; satellitbilder; väderdata; LSTM; CNN; tidsseriein;

   Abstract : Cellular network traffic prediction is a critical challenge for communication providers, which is important for use cases such as traffic steering and base station resources management. Traditional prediction methods mostly rely on historical time-series data to predict traffic load, which often fail to model the real world and capture surrounding environment conditions. READ MORE