New Research Reveals How Long It Actually Takes to Hear Back From a Job Application

A new U.S.-based study shows when employers typically respond to applications and helps job seekers understand when to ...

Clipto.AI Announces New Funding to Accelerate On‑Device AI Innovation

Palo Alto, California - Clipto.AI, a global AI company building the next-generation On-Device Multimodal Content OS, ...

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning

Beijing, Jan. 05, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning ...
EurekAlert!

Multimodal learning-based prediction for nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...
IEEE

Application of a Multimodal Deep Learning Model Based on Recursive Fusion Feature Map With Transformer–TCN for Complex Fault Diagnosis of Flying Wing UAV Actuators

Abstract: This present article proposes a multimodal deep learning model based on recursive feature fusion map (RFFM) and Transformer-temporal convolutional network (TCN), to solve the problem of ...
VentureBeat

New training method boosts AI multimodal reasoning with smaller, smarter datasets

Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning. The ...
Santa Clara University

Global Learning Application FAQs

What are the phases for Global Learning participation? The Global Learning application process is a two-step process, and participation is contingent upon approval by Santa Clara University. Phase 1: ...
IEEE

Incomplete Multi-modal Disentanglement Learning with Application to Alzheimer’s Disease Diagnosis

Abstract: Multi-modal neuroimaging data, including magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (PET), have greatly advanced the computer-aided diagnosis of ...
Frontiers

Multimodal perception-driven decision-making for human-robot interaction: a survey

Multimodal perception is essential for enabling robots to understand and interact with complex environments and human users by integrating diverse sensory data, such as vision, language, and tactile ...