Titlebook: Artificial Intelligence; Second CAAI Internat Lu Fang,Daniel Povey,Ruiping Wang Conference proceedings 2022 The Editor(s) (if applicable) a

ASSAY

Automatic Property Declaration,ers and float-point operations (FLOPs) of DLIC severely limit their application on mobile devices. To reduce the parameters and FLOPs while maintaining the superior compression gain, this paper proposes lightweight algorithms especially for the feature analysis, synthesis, and fusion modules in DLIC

Osteoporosis

Business Framework Implementation,ntly learns multiple dense prediction tasks in a unified multi-task learning architecture that is trained end-to-end. Specifically, the DGMLP consists of (i) a spatial deformable MLP to capture the valuable spatial information for different tasks and (ii) a spatial gating MLP to learn the shared fea

整潔漂亮

直覺(jué)好

拔出

不易燃

contrast-medium

Managed Types, Instances, and Memory,s Microsoft Kinect, the captured RGB-D images provide users with a higher viewing experience, but also pose a higher challenge to the current saliency detection technology. In this paper, we propose a shape-aware saliency object detection approach SASD, manifesting in two aspects: 1) obtaining high

小官

OREX

Managed Types, Instances, and Memory,iew RGB image. Novel view synthesis by neural radiance fields has achieved great improvement with the development of deep learning. However, how to make the method generic across scenes has always been a challenging task. A good idea is to introduce 2D image features as prior knowledge for adaptive

IVORY