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 ...

Meta’s Brain2Qwerty v2 turns thoughts into text, and it doesn’t need brain implants

Meta has unveiled Brain2Qwerty v2, an AI system that converts brain activity into text without surgery, bringing assistive communication a step closer to reality. The Latest Tech News, Delivered to Yo ...
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 ...