Showing 4 open source projects for "fusion"

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    Must Reading on ISAC

    Must Reading on ISAC

    Must Reading Papers, Research Library, Open-Source Code

    A design paradigm and corresponding enabling technologies, in which sensing and comms systems are integrated to efficiently utilize congested wireless/hardware resources, and even to pursue mutual benefits. Waveform Design and Signal Processing Aspects for Fusion of Wireless Communications and Radar Sensing. Supported by IEEE ComSoc ISAC Emerging Technology Initiative (ETI). Integrating Sensing and Communications for Ubiquitous IoT. Include reproducible codes, good papers and a research libary.
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  • 2
    RefineNet

    RefineNet

    RefineNet: Multi-Path Refinement Networks

    RefineNet is a MATLAB-based framework for semantic image segmentation and general dense prediction tasks. It implements the architecture presented in the CVPR 2017 paper RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation and its extended version published in TPAMI 2019. The framework uses multi-path refinement and improved residual pooling to achieve high-quality segmentation results across multiple benchmark datasets. It provides trained models for datasets...
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  • 3
    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. Our work allows computers to recognize objects in images, what is distinctive about our work is that we also recover the 2D outline of objects. Currently we have trained this model to recognize 20 classes. ...
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  • 4

    ISAD

    Individual Synaptic Activity Detection (ISAD)

    ISAD is a peak detection software that detects individual (pre-)synaptic activity in microscopy images from neuronal cultures transfected with pHluorin. It computes synaptic signals from automatically segmented regions of interest and detects peaks that represent vesicle fusion events, thus, pre-synaptic activity. ISAD is based on MWA, which is a continuous wavelet transform based algorithm that employs multiple wavelets and is published as: Sokoll, S., Tönnies, K., and Heine, M. Detection of Spontaneous Vesicle Release at Individual Synapses Using Multiple Wavelets in a CWT-Based Algorithm. Med Image Comput Comput Assist Interv (MICCAI). 2012;15(Pt 1):165-72 ISAD is written in MATLAB and comes with a graphical user interface.
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