IEEE

FPGA Design and Implementation of BCH Encoders and Decoders Using Pipelined Architecture for High Throughput Applications

This paper presents the design and FPGA implementation of a high-throughput BCH (n,k) encoder and decoder using a fully pipelined architecture. Unlike conventional designs based on finite state ...
GitHub

Unifying Computational Imaging via a Multi-Modal Foundation Model

Flux by Black Forest Labs — we use their pretrained diffusion model and autoencoder. JointDiT by Microsoft Research Asia — we adopt and extend their RGBD autoencoder infrastructure. This code was ...
IEEE

GURNet: A Gated U-Shaped Encoder-Decoder Predictor for Reversible Data Hiding

Abstract: The existing deep learning based reversible data hiding (RDH) predictors typically adopt standard convolutions for extracting features, which inherently fails to capture contextual ...
GitHub

MathSnap AI — Handwritten Mathematical Expression Recognition

The encoder employs a DenseNet-B (bottleneck) architecture with three dense blocks separated by transition layers. Each bottleneck layer consists of a 1x1 convolution (expanding to 4x growth rate) ...