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FBR-CNN: A Feedback Recurrent Network for Video Saliency Detection.

, , , , и . MLSP, стр. 1-6. IEEE, (2021)

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Safak Caglayan

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Другие публикации лиц с тем же именем

Exploiting Multi-layer Features Using a CNN-RNN Approach for RGB-D Object Recognition., и . ECCV Workshops (3), том 11131 из Lecture Notes in Computer Science, стр. 675-688. Springer, (2018)Volumetric Object Recognition Using 3-D CNNs on Depth Data., и . IEEE Access, (2018)When CNNs meet random RNNs: Towards multi-level analysis for RGB-D object and scene recognition., , , и . Comput. Vis. Image Underst., (2022)FBR-CNN: A Feedback Recurrent Network for Video Saliency Detection., , , , и . MLSP, стр. 1-6. IEEE, (2021)FBNet: FeedBack-Recursive CNN for Saliency Detection., , , , и . MVA, стр. 1-5. IEEE, (2021)3D convolutional object recognition using volumetric representations of depth data., и . MVA, стр. 125-128. IEEE, (2017)SalFBNet: Learning pseudo-saliency distribution via feedback convolutional networks., , , , и . Image Vis. Comput., (2022)RGB-D SLAM Using Attention Guided Frame Association., , , , , , и . CoRR, (2022)SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolutional Networks., , , , и . CoRR, (2021)SalLiDAR: Saliency Knowledge Transfer Learning for 3D Point Cloud Understanding., , , , и . BMVC, стр. 584. BMVA Press, (2022)