Essays about: "Feedforward networks"

Showing result 1 - 5 of 40 essays containing the words Feedforward networks.

  1. 1. Using Machine Learning to Optimize Near-Earth Object Sighting Data at the Golden Ears Observatory

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

    Author : Laura Murphy; [2023]
    Keywords : Near-Earth Object Detection; Machine Learning; Deep Learning; Visual Transformers;

    Abstract : This research project focuses on improving Near-Earth Object (NEO) detection using advanced machine learning techniques, particularly Vision Transformers (ViTs). The study addresses challenges such as noise, limited data, and class imbalance. READ MORE

  3. 2. Winter Wheat Harvest Prediction Using Primarily Satellite Radar Data from Sentinel-1

    University essay from Lunds universitet/Matematik LTH

    Author : Oliver Persson Bogdanovski; Christoffer Svenningsson; [2023]
    Keywords : Precision Agriculture; Sentinel-1 SAR; Machine Learning; Winter Wheat; Harvest Prediction; RFI-filtering; Despeckling; Mathematics and Statistics;

    Abstract : Aiding farmers with their tremendous task of sustainably and cost-efficiently feeding the world is of utmost importance. Information technology plays a crucial role in supporting farmers and supplying them with accurate information about their crops. READ MORE

  4. 3. Let Us Put Our Brains in the Spotlight – Literally!

    University essay from Lunds universitet/Examensarbeten i molekylärbiologi

    Author : Elsa Karjalainen; [2023]
    Keywords : Biology and Life Sciences;

    Abstract : Neurons are the working force in each vertebrate’s nervous system. These small cells have the important task of transferring information in the form of electrical charges called action potentials. Neurons make it possible for us to sense touch, process our environment, and store memory. READ MORE

  5. 4. Temporal Localization of Representations in Recurrent Neural Networks

    University essay from Högskolan Dalarna/Institutionen för information och teknik

    Author : Asadullah Najam; [2023]
    Keywords : Recurrent Neural Networks RNNs ; Deep Learning; Time Series Prediction; Exploding Values; Gradient Decay; Long Short-Term Memory LSTMs ; Gated Recurrent Units GRUs ; Attention Mechanism; Moving Representations; Localizing Representations;

    Abstract : Recurrent Neural Networks (RNNs) are pivotal in deep learning for time series prediction, but they suffer from 'exploding values' and 'gradient decay,' particularly when learning temporally distant interactions. Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) have addressed these issues to an extent, but the precise mitigating mechanisms remain unclear. READ MORE

  6. 5. Monocular 3D Human Pose Estimation

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

    Author : Robert Rey; [2023]
    Keywords : 3D Human Pose Estimation; Monocular Images; Deep Learning; Artificial Neural Networks; 3D Människokroppspositionsuppskattning; Monokulära bilder; Djupinlärning; Konstgjorda neurala nätverk;

    Abstract : The focus of this work is the task of 3D human pose estimation, more specifically by making use of key points located in single monocular images in order to estimate the location of human body joints in a 3D space. It was done in association with Tracab, a company based in Stockholm, who specialises in advanced sports tracking and analytics solutions. READ MORE