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Titlebook: Neural Information Processing; 28th International C Teddy Mantoro,Minho Lee,Achmad Nizar Hidayanto Conference proceedings 2021 Springer Nat

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Deep Supervised Hashing by Classification for Image Retrievaluirement. With the development of deep learning, a series of deep supervised methods were proposed for end-to-end binary code learning. However, the similarity between each pair of images is simply defined by whether they belong to the same class or contain common objects, which ignores the heteroge
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Coarse-to-Fine Visual Place Recognitiony conducted as an image retrieval task. Currently, global-based and local-based descriptors are two mainstream representations to solve VPR. However, they still struggle against viewpoint change, confusion from similar patterns in different places, or high computation complexity. In this paper, we p
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Integrating Rich Utterance Features for Emotion Recognition in Multi-party Conversationsxt, the speaker-specific information, and the interaction within a conversation. To this end, we propose a graph-based multi-task learning network to integrate these utterance features for emotion recognition in multi-party conversations. First, we represent each utterance and each speaker as a node
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Vehicle Image Generation Going Well with the Surroundingsr, we propose an approach for vehicle image generation in real-world scenes. Using a subnetwork based on a precedent work of image completion, our model makes the shape of an object. Details of objects are trained by additional colorization and refinement subnetworks, resulting in a better quality o
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