Essays about: "Deep Convolutional Neural Network"

Showing result 1 - 5 of 407 essays containing the words Deep Convolutional Neural Network.

1. 1. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

   University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Author : Nikolaos Staikos; [2024]
   Keywords : Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

   Abstract : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. READ MORE

3. 2. Learning a Grasp Prediction Model for Forestry Applications

   University essay from Umeå universitet/Institutionen för fysik

   Author : Elias Olofsson; [2024]
   Keywords : Forwarder; Autonomous grasping; Deep learning; Multibody dynamics; Convolutional neural network;

   Abstract : Since the advent of machine learning and machine vision methods, progress has been made in tackling the long-standing research question of autonomous grasping of arbitrary objects using robotic end-effectors. Building on these efforts, we focus on a subset of the general grasping problem concerning the automation of a forwarder. READ MORE

4. 3. Evaluation of Deep Q-Learning Applied to City Environment Autonomous Driving

   University essay from Uppsala universitet/Signaler och system

   Author : Jonas Wedén; [2024]
   Keywords : Machine Learning; ML; Reinforcement Learning; RL; Neural Network; Deep Learning; Autonomous Vehicle; Vehicle; CARLA; Convolutional Neural Network; CNN; Precisit; Q-learning; Deep Q-learning; DQN;

   Abstract : This project’s goal was to assess both the challenges of implementing the Deep Q-Learning algorithm to create an autonomous car in the CARLA simulator, and the driving performance of the resulting model. An agent was trained to follow waypoints based on two main approaches. READ MORE

5. 4. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks

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

   Author : Xinchen Wang; [2024]
   Keywords : Deep Learning; Semantic segmentation; Network optimization; Network pruning; Torch Pruning; YOLOv8; Network Depth; Djup lärning; Semantisk segmentering; Nätverksoptimering; Nätverksbeskärning; Fackelbeskärning; YOLOv8; Nätverksdjup;

   Abstract : 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. READ MORE

6. 5. Virtual H&E Staining Using PLS Microscopy and Neural Networks

   University essay from Lunds universitet/Matematik LTH

   Author : Sally Vizins; Hanna Råhnängen; [2024]
   Keywords : Deep learning; Virtual staining; Skin tissue; Hematoxylin Eosin; H E; Pathology; Carcinoma; Point light source illumination; Neural Networks; GANs; Generative adversarial networks; CNNs; Convolutional neural networks; Relativistic generative adversarial network; Unet; Digital microscopy; Attention-Unet; Dense-Unet; Mathematics and Statistics;

   Abstract : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. READ MORE