BACKBONE NETWORK LEARNING METHOD AND SYSTEM BASED ON SELF-SUPERVISED LEARNING AND MULTI-HEAD FOR VISUAL INTELLIGENCE

    公开(公告)号:US20240394546A1

    公开(公告)日:2024-11-28

    申请号:US18225304

    申请日:2023-07-24

    Abstract: There is provided a learning method and system of a backbone network for visual intelligence based on self-supervised learning and multi-head. A network learning system according to an embodiment generates a plurality of first modified vectors by modifying a first feature vector outputted from a teacher network, generates a plurality of second modified vectors by modifying a second feature vector outputted from a student network, calculates a loss by using the first modified vectors and the second modified vectors, and optimizes parameters of the student network. Accordingly, the effect of learning by knowledge distillation may be enhanced by training the backbone network for visual intelligence like group learning is performed by various teacher networks and student networks.

    TRAINING METHOD OF MULTI-TASK INTEGRATED DEEP LEARNING MODEL

    公开(公告)号:US20250148270A1

    公开(公告)日:2025-05-08

    申请号:US18644636

    申请日:2024-04-24

    Abstract: There is provided a training method of a multi-task integrated deep learning model. A multi-task integrated deep learning model training method according to an embodiment may generate training data for a plurality of visual intelligence tasks from visual data in a batch, and may train a multi-task integrated deep learning model which performs a plurality of visual intelligence tasks by using the generated training data. Accordingly, training data for training an integrated deep learning model which performs various visual intelligence tasks is generated in a batch through multi-data conversion kernels, so that appropriate training data for performing multiple tasks may be easily obtained and effective training of a multi-task integrated deep learning model is possible.

    METHOD AND SYSTEM FOR ACQUIRING VISUAL EXPLANATION INFORMATION INDEPENDENT OF PURPOSE, TYPE, AND STRUCTURE OF VISUAL INTELLIGENCE MODEL

    公开(公告)号:US20250095341A1

    公开(公告)日:2025-03-20

    申请号:US18741942

    申请日:2024-06-13

    Abstract: There are provided a method and a system for acquiring visual explanation information independent of the purpose, type, and structure of a visual intelligence model. The visual explanation information acquisition system of the visual intelligence model according to an embodiment may input N transformed images which are generated by diversifying an input image to a deep learning-based visual intelligence model and may acquire outputted results, may generate attributes of the visual intelligence model from the acquired results, may derive, from losses of the visual intelligence model which are calculated from the generated attributes, basic data for generating a visual explanation map for visually explaining a result derivation rationale of the visual intelligence model, and may generate a visual explanation map from the derived basic data. Accordingly, visual explanation information may be acquired from various visual intelligence models through one system independently of the purpose, type, and structure of the visual intelligence model.

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