Showing 4 open source projects for "split"

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    ESP3

    ESP3

    Fisheries acoustics data processing software

    ...ESP3 is an open-source software package for visualizing and processing fisheries acoustics data, developed by the deepwater fisheries acoustics team at NIWA (Wellington, New Zealand). # What can ESP3 do? ESP3 is designed for single-beam and split-beam data. Currently supported data formats are SIMRAD (.raw) and a small number of other formats. The software allows calibration and echo-integration and a number of algorithms are coded in, including bad pings identification, automated bottom detection, single targets identification and tracking, schools identification, etc. ...
    Downloads: 4 This Week
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  • 2
    NTU RGB-D

    NTU RGB-D

    Info and sample codes for "NTU RGB+D Action Recognition Dataset"

    ...The repository also contains MATLAB / Python demo scripts for loading, visualizing, and processing skeleton data, mapping between modalities, and handling dataset structure. Multi-modal action recognition dataset, RGB, depth, infrared, skeletal data. Split into background / evaluation sets for one-shot evaluation (in the extended dataset).
    Downloads: 0 This Week
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  • 3
    VGGFace2

    VGGFace2

    VGGFace2 Dataset for Face Recognition

    ...It consists of 3.31 million images covering 9,131 subjects, with an average of over 360 images per subject. The dataset was collected from Google Image Search, ensuring a wide diversity in ethnicity, profession, and real-world conditions. It is split into a training set with 8,631 identities and a test set with 500 identities, making it suitable for benchmarking and large-scale model training. Alongside the dataset, the repository provides pre-trained models based on ResNet-50 and SE-ResNet-50 architectures, trained with both MS-Celeb-1M pretraining and fine-tuning on VGGFace2. ...
    Downloads: 16 This Week
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  • 4
    Omniglot

    Omniglot

    Omniglot data set for one-shot learning

    ...Includes stroke data (time-sequenced coordinates) per sample. The repository is intended as a benchmark dataset in few-shot / meta-learning research, not as a plug-and-play detection or classification engine. Pre-split “background” and “evaluation” alphabets for standard benchmarking.
    Downloads: 0 This Week
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