Showing 9 open source projects for "neural network visualiser"

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    CNN for Image Retrieval
    cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that...
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  • 2
    SFD

    SFD

    S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017

    S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with modifications tailored for face detection tasks. ...
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  • 3
    GTK+ IOStream

    GTK+ IOStream

    GTK+iostream, Data plots, ORB, Neural Networks, WSOLA

    Create GTK+ interfaces using IOStream style code. Its simple and quick! Also providing simple data plotting (similar to Matlab/Octave), ORB (Object Request Broker), and Neural Network computations. You can create GTK+ GUIs in a few lines of code. Labels<<"Thanks for reading"; (HBox<<Labels).show(); or even one line : (HBox() << (Labels()<<"Thanks for reading")).show(); Inline code destructs the classes, but leaves the widgets/callbacks operating. This is great for embedded memory saving code. ...
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  • 4
    Face Verification Experiment

    Face Verification Experiment

    Original Caffe Version for LightCNN-9. Highly recommend to use PyTorch

    face_verification_experiment is a research repository focused on experiments in face verification using deep learning. It provides implementations and scripts for testing different neural network architectures and training strategies on face recognition and verification tasks. The project is designed to help researchers and practitioners evaluate the performance of models on standard datasets and explore techniques for improving accuracy. By offering experimental setups, it enables reproducibility and comparative study of face verification approaches. ...
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  • 5
    CRFasRNN

    CRFasRNN

    Semantic image segmentation method described in the ICCV 2015 paper

    CRF-RNN is a deep neural architecture that integrates fully connected Conditional Random Fields (CRFs) with Convolutional Neural Networks (CNNs) by reformulating mean-field CRF inference as a Recurrent Neural Network. This fusion enables end-to-end training via backpropagation for semantic image segmentation tasks, eliminating the need for separate, offline post-processing steps.
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  • 6
    Face recognition using BPNN. Contains 1.Face recognition using Back propagation neural network (customize code) code using matlab. 2. Face recognition using Back propagation network (builtin) code using matlab.Project closed for now,Adeel Raza Azeemi
    Downloads: 0 This Week
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  • 7

    Speedy Composer

    Speedy Composer – Artificial Neural Network Melody Composer.

    Thank you for your interest in Speedy Composer. Speedy Composer is an automated application for composing melodies for Speedy Net members. We recently made changes to the source code of Speedy Net, and converted it into the Python language and Django framework. Since Speedy Composer was originally written in PHP, it is not adapted to work with Speedy Net in its current form. So unfortunately we were forced to temporarily close the app Speedy Composer. But don't worry, we kept backups of all...
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  • 8
    The project goal is to develop several IP cores that would implement artificial neural networks using FPGA resources. These cores will be designed in such a way to allow easy integration in the Xilinx EDK framework.
    Downloads: 0 This Week
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  • 9
    This tool allows to compute LOLIMOT models. LOLIMOT models are also called neuro-fuzzy models or fast neural network models. This tool can export the model into C, C++, Matlab.
    Downloads: 1 This Week
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