IEEE

Exploring Transformer and Multilabel Classification for Remote Sensing Image Captioning

Abstract: High-resolution remote sensing images are now available with the progress of remote sensing technology. With respect to popular remote sensing tasks, such as scene classification, image ...
IEEE

Temporal Convolutional and Fusional Transformer Model With Bi-LSTM Encoder-Decoder for Multi-Time-Window Remaining Useful Life Prediction

Abstract: Health prediction is crucial for ensuring reliability, minimizing downtime, and optimizing maintenance in industrial systems. Remaining Useful Life (RUL) prediction is a key component of ...
GitHub

LEFormer: A Hybrid CNN-Transformer Architecture for Accurate Lake Extraction from Remote Sensing Imagery

The repository contains official PyTorch implementations of training and evaluation codes and pre-trained models for our ICASSP 2024 paper LEFormer. Figure 1: Overview architecture of LEFormer, ...
note

Gemma 4 12B In-Depth: A New Model Bringing Full-Scale Multimodality to Laptops with an Encoder-Free Design

Gemma 4 12B is a new model in the Gemma 4 family announced by Google on June 3, 2026. It is positioned as an "encoder-free unified multimodal model optimized for laptops." The official blog (Google ...
Virtualization Review

Using Speculative Decoding to Improve Chatbot Performance

Speculative decoding can help AI chatbots improve throughput and reduce hardware demand by using a smaller model to draft tokens that a larger model validates.
note

A Story About Meeting Three Unique Characters After Learning About Transformers

When learning deep learning, one architecture you cannot avoid is Transformer. Born from the 2017 paper "Attention Is All You Need," this technology supports the foundation of the AI you use today, ...
GitHub

Transformer Architecture: Self-Attention, Classification, Causal LM & PDF Translation

Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills ...
Frontiers

DPCrossU-Net: a dual-branch parallel CNN–Transformer network for lung nodule segmentation

We propose DPCrossU-Net, a dual-branch parallel encoder–decoder network that integrates convolutional and Vision Transformer representations. The encoder employs parallel CNN and ViT branches with a ...