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Showing 1 to 8 of 8 for “"Convolutional Neural Net"”.

  1. Control and Convolutional Neural Net Based Pose Estimation for On-Orbit Assembly

    … feasibility. TESSERAE, or Tessellated Electromagnetic Space Structures for Exploration of Reconfigurable Adaptive Environments, a project out of the MIT Media Lab Space Exploration Initiative, is a multi-year research effort to develop a set of self-assembling, decentralized tiles that use …

    mit Repository record for Control and Convolutional Neural Net Based Pose Estimation for On-Orbit Assembly (opens in a new tab)

  2. Convolutional Neural Net Models and Image Processing Methods for Predicting Surgical Site Infection

    … to capture an image of a wound and then apply a convolutional neural network (CNN) model to identify features of infection. For this thesis, I have explored both RGB images captured using a mobile phone camera and also thermal images captured using an external thermal camera module. The data for …

    mit Repository record for Convolutional Neural Net Models and Image Processing Methods for Predicting Surgical Site Infection (opens in a new tab)

  3. Design and evaluation of a novel convolutional neural network for short-term vehicle multi-traffic prediction

    … congestion state. In this thesis, we propose a convolutional neural net-work model that performs traffic forecasting for all three parameters, using historical integrated traffic data over a large area. The proposed model also predicts all three parameters for all 5-minute intervals from the …

    uoit Repository record for Design and evaluation of a novel convolutional neural network for short-term vehicle multi-traffic prediction (opens in a new tab)

  4. Interpretable Deep Image Denoiser by Unrolling Graph Laplacian Regularizer

    … minima. This thesis proposes an image denoising neural net constructed by unrolling an iterative algorithm solving a maximum a posteriori (MAP) optimization problem regularized using a graph Laplacian prior. To guarantee a minimum level of performance, we initialize the network to a known …

    york Repository record for Interpretable Deep Image Denoiser by Unrolling Graph Laplacian Regularizer (opens in a new tab)

  5. Applying Artificial Intelligence and Mobile Technologies to Enable Practical Screening for Diabetic Retinopathy

    … of an image processing pipeline and a neural net algorithm that automatically tests image quality (based on brightness, color, and amount of blur), rejects poor quality images, and re-formats each image into a standard image resolution. In order to create a generalized model, I used a …

    mit Repository record for Applying Artificial Intelligence and Mobile Technologies to Enable Practical Screening for Diabetic Retinopathy (opens in a new tab)

  6. Deriving Structural Insights About Mesoscale Chromatin Folding Using Coarse-Grained Oligonucleosome Modeling

    … of inter-nucleosome interactions. Using a 1D convolutional neural net trained on predicted RICC-seq signal, we show that nucleosome repeat lengths consistent with orthogonal assays can be extracted from experimental RICC-seq data. Our framework thus provides a suite of analysis tools that add …

    rockefeller Repository record for Deriving Structural Insights About Mesoscale Chromatin Folding Using Coarse-Grained Oligonucleosome Modeling (opens in a new tab)

  7. Computer vision based posture estimation and fall detection.

    … the foreground images were used in a Convolutional Neural Network (CNN) to recognise different poses. The RGB and the Depth images were captured from a Kinect Sensor. The fusion of RGB and Depth images were explored for feeding to a convolutional neural net- work. Depth together with …

    bournemouth Repository record for Computer vision based posture estimation and fall detection. (opens in a new tab)

  8. Classification of road side material using convolutional neural network and a proposed implementation of the network through Zedboard Zynq 7000 FPGA

    In recent years, Convolutional Neural Networks (CNNs) have become the state-of- the-art method for object detection and classi cation in the eld of machine learning and arti cial intelligence. In contrast to a fully connected network, each neuron of a convolutional layer of a CNN is connected to …

    iupui Repository record for Classification of road side material using convolutional neural network and a proposed implementation of the network through Zedboard Zynq 7000 FPGA (opens in a new tab)