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Found 18 papers, 7 papers with code
A Probabilistic Hadamard U-Net for MRI Bias Field Correction
Random samples drawn from latent space are then incorporated with a prototypical corrected image to generate multiple plausible images.
The Blind Normalized Stein Variational Gradient Descent-Based Detection for Intelligent Massive Random Access
Furthermore, with the assistance of the block MHT layer, the proposed blind normalized SVGD algorithm achieves a higher preamble detection accuracy and throughput than other state-of-the-art detection methods.
Generate E-commerce Product Background by Integrating Category Commonality and Personalized Style
Furthermore, for products with specific and fine-grained requirements in layout, elements, etc, a Personality-Wise Generator is devised to learn such personalized style directly from a reference image to resolve textual ambiguities, and is trained in a self-supervised manner for more efficient training data usage.
Planning and Rendering: Towards End-to-End Product Poster Generation
At the planning stage, we propose a PlanNet to generate the layout of the product and other visual components considering both the appearance features of the product and semantic features of the text, which improves the diversity and rationality of the layouts.
A novel asymmetrical autoencoder with a sparsifying discrete cosine Stockwell transform layer for gearbox sensor data compression
In comparison to the linear layer, the DCST layer reduces the number of trainable parameters and improves the accuracy of data reconstruction.
Domain Generalization with Fourier Transform and Soft Thresholding
However, it neglects background interference in the amplitude spectrum.
Electroencephalogram Sensor Data Compression Using An Asymmetrical Sparse Autoencoder With A Discrete Cosine Transform Layer
The latent space data is transmitted to the receiver.
Stein Variational Gradient Descent-based Detection For Random Access With Preambles In MTC
Traditional preamble detection algorithms have low accuracy in the grant-based random access scheme in massive machine-type communication (mMTC).
Mutual Query Network for Multi-Modal Product Image Segmentation
Product image segmentation is vital in e-commerce.
Relation-Aware Diffusion Model for Controllable Poster Layout Generation
To advance research in this field, we have constructed a poster layout dataset named CGL-Dataset V2.
A Hybrid Quantum-Classical Approach based on the Hadamard Transform for the Convolutional Layer
In this paper, we propose a novel Hadamard Transform (HT)-based neural network layer for hybrid quantum-classical computing.
Multichannel Orthogonal Transform-Based Perceptron Layers for Efficient ResNets
Trainable soft-thresholding layers, that remove noise in the transform domain, bring nonlinearity to the transform domain layers.
CBNet: A Plug-and-Play Network for Segmentation-Based Scene Text Detection
Recently, segmentation-based methods are quite popular in scene text detection, which mainly contain two steps: text kernel segmentation and expansion.
DCT Perceptron Layer: A Transform Domain Approach for Convolution Layer
In this paper, we propose a novel Discrete Cosine Transform (DCT)-based neural network layer which we call DCT-perceptron to replace the $3\times3$ Conv2D layers in the Residual neural Network (ResNet).
Real-time Wireless ECG-derived Respiration Rate Estimation Using an Autoencoder with a DCT Layer
To improve the estimation precision, we propose a neural network that uses a novel Discrete Cosine Transform (DCT) layer to denoise and decorrelates the data.
Semantic Relationships Guided Representation Learning for Facial Action Unit Recognition
Specifically, by analyzing the symbiosis and mutual exclusion of AUs in various facial expressions, we organize the facial AUs in the form of structured knowledge-graph and integrate a Gated Graph Neural Network (GGNN) in a multi-scale CNN framework to propagate node information through the graph for generating enhanced AU representation.
Learning Chained Deep Features and Classifiers for Cascade in Object Detection
In this CC-Net, the cascaded classifier at a stage is aided by the classification scores in previous stages.
