One of the biggest problems facing modern microelectronics is that computer chips can no longer be made arbitrarily smaller ...
Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...
Progress will come from systems that can combine language understanding with explicit spatial and structural reasoning.
Abstract: The amalgamation of millimeter-wave (mmWave) communications and multiple-input multiple-output (MIMO) orthogonal time frequency space (OTFS) systems holds significant promise for ...
The year 2022 has been declared by Pedro Sanchez, President of Spain, as the Year of Ramon y Cajal on the 170th anniversary ...
Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...
Abstract: As skin diseases continue to emerge worldwide, there is a growing need for fast and accurate diagnosis. However, access to dermatologists remains limited, especially in remote and ...
Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry ...
For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...
A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...
The 2026 International Production & Processing Expo (IPPE) is about to open its doors, and Shanghai Xiashu Intelligent ...
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