Showing 4 open source projects for "no-code-app-builders"

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    Exposure Correction

    Exposure Correction

    Learning multi-scale deep model correcting over- and under- exposed

    ...This allows the model to preserve fine details while correcting global lighting inconsistencies. The repository includes pre-trained models, datasets, and training/testing code to enable reproducibility and experimentation. By leveraging this framework, researchers and developers can apply exposure correction to a wide range of natural images, improving visual quality without manual editing. The project serves both as a research reference and a practical tool for computational photography and image enhancement.
    Downloads: 2 This Week
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  • 2
    Spheroid_segmentation

    Spheroid_segmentation

    Deep learning networks for spheroid segmentation

    To accelerate the analysis of tumors' spheroids, different deep learning networks were trained to automatize the segmentation process. The code provides the trained networks based on Vgg16, Vgg19, ResNet18, and ResNet50 ready to be used for segmentation purposes. It also provides Matlab functions ready to be used to train new networks, segment new images, and measure the quality of the training using different quantitative parameters.
    Downloads: 0 This Week
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  • 3
    MatlabFunc

    MatlabFunc

    Matlab codes for feature learning

    ...These functions cover areas such as matrix operations, optimization, data processing, and visualization, making them broadly applicable across different research domains. The project is intended to provide reusable and adaptable MATLAB code that can save time for researchers and students working on experimental or applied projects. By consolidating these tools in one place, MatlabFunc serves as a practical reference and toolkit for both academic and engineering purposes. Contributions and improvements from the community are encouraged, allowing the repository to grow into a richer resource over time.
    Downloads: 1 This Week
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  • 4
    Detect and Track

    Detect and Track

    Code release for "Detect to Track and Track to Detect", ICCV 2017

    ...The framework unifies object detection and tracking into a single pipeline, allowing detection to support tracking and tracking to enhance detection performance. Built upon a modified version of R-FCN, the code provides implementations using backbone networks such as ResNet-50, ResNet-101, ResNeXt-101, and Inception-v4, with results demonstrating state-of-the-art accuracy on the ImageNet VID dataset. The repository includes MATLAB-based training and testing scripts, along with pre-trained models and pre-computed region proposals for reproducibility. ...
    Downloads: 0 This Week
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