Meta’s Brain2Qwerty v2 offers a breakthrough non-invasive brain-to-text AI model with 61% word accuracy, challenging Neuralink’s invasive methods by decoding brain signals into text without surgery.

Species distribution models (SDMs) often overlook critical spatial heterogeneity and multiscale environmental patterns, which limit their predictive accuracy for species occurrences. We demonstrate ...

1 Department of Computer Engineering, School of Engineering, The University of Jordan, Amman, Jordan. 2 Department of Data Science and Artificial Intelligence, Faculty of Information Technology, ...

With the basic structure and parameters of the model remaining unchanged, this section analyzes and compares two types of network structures with input image sizes of 128 × 128 and 256 × 256. The ...

Electroencephalogram-based brain-computer interfaces (BCIs) hold promise for healthcare applications but are hindered by cross-subject variability and limited data. This article proposes a multi-task ...

All resulting images and pre-trained models are available in the provided links. 11/26/2024 Code for real haze and haze4k are released. 07/22/2024 We release the code for dehazing (ITS/OTS), desnowing ...

Abstract: This paper focuses on performance analysis of convolution encoder based on FPGA. With the big quantity of applications now a days, that use digital ...

[1] Image compression techniques survey Abir Jaafar, Ali Al-Fayadh, Naeem Radi Hussain. (2018). Image compression techniques: A survey in lossless and lossy ...

Abstract: In this paper, canonical convolutional encoders are studied for unequal error protection (UEP) from an algebraic theoretical viewpoint. We show that for any ...