The Financial Express

How Mark Zuckerberg’s brain-to-text AI model promises to outshine Elon Musk’s Neuralink

Meta’s Brain2Qwerty v2 offers a breakthrough non-invasive brain-to-text AI model with 61% word accuracy, challenging ...
IEEE

MaS-TransUNet: A Multiattention Swin Transformer U-Net for Medical Image Segmentation

Abstract: U-shaped encoder-decoder models have excelled in automatic medical image segmentation due to their hierarchical feature learning capabilities, robustness, and upgradability. Purely CNN-based ...
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 ...
Tech Times

Baidu OCR Breaks Long-Document Memory Wall: New Architecture Beats DeepSeek

Open-source OCR from Baidu eliminates the GPU memory wall that limits long-document parsing. Unlimited OCR uses a constant KV ...
GitHub

Full Sequence-to-Sequence Encoder-Decoder Transformer for Neural Machine Translation

This repository contains a mathematically precise implementation of the original "Attention Is All You Need" Transformer architecture. Built entirely from scratch, the model maps English source ...
GitHub

NVIDIA-AI-IOT/nanosam

NanoSAM is a Segment Anything (SAM) model variant that is capable of running in 🔥 real-time 🔥 on NVIDIA Jetson Orin Platforms with NVIDIA TensorRT. NanoSAM is trained by distilling the MobileSAM ...
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 ...