Semiconductor Engineering2d
Transistor Sizing Approach for OTA Circuits Using a Transformer Architecture
A  new technical paper titled “Accelerating OTA Circuit Design: Transistor Sizing Based on a Transformer Model and ...
unite1d
Transformers and Beyond: Rethinking AI Architectures for Specialized Tasks
In 2017, a significant change reshaped Artificial Intelligence (AI). A paper titled Attention Is All You Need introduced ...
IEEE3d
A Cross-Attention Multi-Scale Performer with Gaussian Bit-Flips for File Fragment Classification
To address this limitation, we propose the Cross-Attention Multi-Scale Performer (XMP) model, which integrates the attention mechanisms of transformer encoders with the feature extraction capabilities ...
Electronic Design3d
How to Create Smaller, Safer, and Scalable Robotic Designs
Designing robots requires precision and flexibility. Advanced motion control via encoder systems, sensors, and gate-driver ...
GitHub3d
README.md
Pedestrian Intention Estimation using stacked Transformers Encoders. This model is inspired by the SF-GRU model and use it to generate the scene features. Python 3.6.9 Numpy 1.19.5 Pytorch 1.9.1 ...
GitHub6d
A modern diagram scripting language that turns text to diagrams.
For detailed installation docs ... In addition to being a runnable CLI tool, D2 can also be used to produce diagrams from Go programs. For examples, see ./docs/examples/lib. This blog post also demos ...
Frontiers6d
MIHIC: a multiplex IHC histopathological image classification dataset for lung cancer immune microenvironment quantification
CoaT_tiny (54): is capable of acquiring meaningful representations through a modularized architecture. It introduces a co-scale mechanism to image transformer by maintaining encoder branches at ...