: This indicates the data is part of a temporal sequence , likely a single frame extracted from a video file for analysis. Use Case: Feature Extraction
: This is a unique hash . In systems like GitHub or data versioning tools, this ensures that even if two files have the same name, their specific contents are distinguished. 150x150_623c9edd9fa11016d4bc76e2393078b9_frame_...
: Normalizing image sizes for consistent training of a model. Summary Feature Table Value/Type Dimensions 150 x 150 pixels Uniform input size for ML models Source ID Alphanumeric Hash Traceability to the original asset Data Type Video Frame Sequential data for temporal analysis Common Format .jpg, .png, or .npy Standard image or numpy array storage : This indicates the data is part of
For a frame labeled like this, a developer might be performing: : Normalizing image sizes for consistent training of a model
In technical contexts like those discussed on IEEE Xplore , "informative features" refer to the specific data points—like edges, textures, or keypoints—extracted from a frame to help a machine make a decision.