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Found 9 papers, 2 papers with code
Scribble Hides Class: Promoting Scribble-Based Weakly-Supervised Semantic Segmentation with Its Class Label
In this study, we propose a class-driven scribble promotion network, which utilizes both scribble annotations and pseudo-labels informed by image-level classes and global semantics for supervision.
Deep Autoencoder-based Z-Interference Channels with Perfect and Imperfect CSI
The proposed structure significantly enhances the performance of the ZIC both for the perfect and imperfect CSI.
Multi-level Asymmetric Contrastive Learning for Medical Image Segmentation Pre-training
In this work, we propose a novel asymmetric contrastive learning framework named JCL for medical image segmentation with self-supervised pre-training.
3D Implicit Transporter for Temporally Consistent Keypoint Discovery
To address this issue, the Transporter method was introduced for 2D data, which reconstructs the target frame from the source frame to incorporate both spatial and temporal information.
Branches Mutual Promotion for End-to-End Weakly Supervised Semantic Segmentation
Existing methods adopt an online-trained classification branch to provide pseudo annotations for supervising the segmentation branch.
Fully-integrated multipurpose microwave frequency identification system on a single chip
We demonstrate a fully-integrated multipurpose microwave frequency identification system on silicon-on-insulator platform.
SVD-Embedded Deep Autoencoder for MIMO Communications
SVDembedded DAE largely outperforms theoretic linear precoding in terms of BER.
Multi-Objective DNN-based Precoder for MIMO Communications
Numerical results demonstrate that, compared to the conventional solutions, the proposed DNN-based precoder reduces on-the-fly computational complexity more than an order of magnitude while reaching near-optimal performance (99. 45\% of the averaged optimal solutions).
Deep Learning based Precoding for the MIMO Gaussian Wiretap Channel
A novel precoding method based on supervised deep neural networks is introduced for the multiple-input multiple-output Gaussian wiretap channel.
