The Chosun Ilbo on MSN

Universities bridge AI education gap for regional students

Recently, in a lecture room at the Daegu Startup Hub in Dong-gu, Daegu, Kim Soo-pil, a senior researcher at the Daegu ...
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 ...
The Manila Times

WiMi Develops Quantum Convolutional Neural Network Model for Classical Data Classification

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ('WIMI' or the 'Company'), a leading global Hologram Augmented Reality ('AR') Technology provider, has completed systematic benchmark testing on fully ...
IEEE

Computationally Efficient Single Layer Transformer Convolutional Encoder for Accurate Price ...

Abstract: Predicting the accurate future price of the agricultural crops is important to avoid overproduction or shortages in the food supply chain. To obtain accurate predictions, the process usually ...
Frontiers

A resource-efficient quantum convolutional neural network

Quantum Convolutional Neural Network (QCNN) has achieved significant success in solving various complex problems, such as quantum many-body physics and image recognition. In comparison to the ...
C&EN

Patch-Based Convolutional Encoder: A Deep Learning Algorithm for Spectral Classification ...

State Key Laboratory of Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen ...
Scientific Research Publishing

Method of Multi-Mode Sensor Data Fusion with an Adaptive Deep Coupling Convolutional Auto ...

To address the difficulties in fusing multi-mode sensor data for complex industrial machinery, an adaptive deep coupling convolutional auto-encoder (ADCCAE) fusion method was proposed. First, the ...
Frontiers

Hierarchical Sparse Coding of Objects in Deep Convolutional Neural Networks

Recently, deep convolutional neural networks (DCNNs) have attained human-level performances on challenging object recognition tasks owing to their complex internal representation. However, it remains ...