We introduce hierarchical classification based on voting criteria with structural features to classify 62 character classes into different smaller classes. We ...
We introduce hierarchical classification based on voting criteria with structural features to classify 62 character classes into different smaller classes. We ...
To interpret deep neural networks, one main approach is to dissect the visual input and find the prototypical parts responsible for the classification.
We introduce hierarchical classification based on voting criteria with structural features to classify 62 character classes into different smaller classes. We ...
Oct 28, 2024 · We explore the benefits of these models to incorporate contextual data for action recognition in two different ways: (1) evaluating the effect ...
Aug 17, 2022 · In this paper, we propose a two-phase multi-expert classification method for human action recognition by means of super-class learning and without any extra ...
Missing: Character | Show results with:Character
The game-changing feature that makes deep learning more accessible. Solving computer vision problem of Screw & Nut recognition with hierarchical classification.
Jan 1, 2023 · We propose Hierarchical ProtoPNet: an interpretable network that explains its reasoning process by considering the hierarchical relationship ...
Missing: Character | Show results with:Character
Oct 22, 2024 · Classification strategy based on the Hopfield neural networks and image processing methods are described. The characters for recognition are ...
Our method contains two steps. The first stage performs the classification of the input video into a group of activities. The second level classification ...