Titlebook: Cognitive Computation and Systems; First International Fuchun Sun,Jianmin Li,Zhongyi Chu Conference proceedings 2023 The Editor(s) (if app

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painkillers

Infect

A Novel Autoencoder for?Task-Driven Object Segmentationds can only recognize and segment one class of objects, but cannot segment the other classes of objects in the same image. To address this issue, this paper proposes a novel autoencoder to perform task-driven object segmentation, in which a control signal is added to the decoder to determine which c

玩忽職守

Feedback Attention-Augmented Bilateral Network for?Amodal Instance Segmentationarts of each object instance. Many modern computer vision methods demonstrate excellent performance by using the mechanism of looking and thinking twice and the attention mechanism. In this paper, we propose a feedback attention-augmented bilateral network. Specifically, after the convolutional netw

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發(fā)源

PointNetX: Part Segmentation Based on PointNet Promotionet, a pioneer in point cloud processing, uses max pooling to address the disorder of point clouds. However, PointNet‘s method of mapping points to high-dimensional space, and then obtaining global features through maximum pooling still leads to a large loss of feature information. To this end, we su

發(fā)源

Platelet

insolence

Shape and?Pose Reconstruction of?Robotic In-Hand Objects from?a?Single Depth Cameraritically important for robotic in-hand manipulation. However, in-hand objects have self-occlusion, making it challenging to perceive their complete shape and posture. To address this challenge, this work proposed a point-clouds processing framework to achieve shape completion and pose estimation of

蒸發(fā)

“Gongzhu” Strategy Based on Convolutional Neural Networkd-showing and card-playing. The behavior of card-showing determines the strategy of card-playing, and the whole game process is highly reversible. This paper proposes a deep learning-based game algorithm of “Gongzhu”. According to the functional characteristics, the network structure of card-showing