Semiconductor Engineering

Multimodal LLM Assistant for Chip Physical Design (National Taiwan Univ., UCLA, NVIDIA)

A new technical paper titled “Multimodal Chip Physical Design Engineer Assistant” was published by researchers at National ...
IEEE

Lightweight Multimodal Emotion Recognition for Companion Robots: A Deep Learning Framework Integrating Facial and Speech Features

Abstract: This paper presents a lightweight multimodal deep learning framework for real-time emotion recognition on resource-constrained companion robots, exemplified by Zenbo Junior II. The framework ...
Frontiers

Diagnostic performance and generalizability of deep learning for multiple retinal diseases using bimodal imaging of fundus photography and optical coherence tomography

Purpose: To develop and evaluate deep learning (DL) models for detecting multiple retinal diseases using bimodal imaging of color fundus photography (CFP) and optical coherence tomography (OCT), ...
eLife

Comprehensive Neural Representations of Naturalistic Stimuli through Multimodal Deep Learning

State Key Laboratory of Cognitive Neuroscience and Learning, and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China The study leverages a multimodal machine learning ...
eLife

Comprehensive Neural Representations of Naturalistic Stimuli through Multimodal Deep Learning

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...
C&EN

Multimodal Deep Learning for Generating Potential Anti-Dengue Peptides

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Furthermore, stacking neural network approaches have exhibited ...
marktechpost

Zhipu AI Releases GLM-4.5V: Versatile Multimodal Reasoning with Scalable Reinforcement Learning

Zhipu AI has officially released and open-sourced GLM-4.5V, a next-generation vision-language model (VLM) that significantly advances the state of open multimodal AI. Based on Zhipu’s 106-billion ...
IEEE

A Deep Learning Multimodal Fusion-Based Method for Cell and Nucleus Segmentation

Abstract: In recent years, deep learning has been widely utilized in the fields of biomedical image segmentation and cellular image analysis. Supervised deep neural networks trained on annotated data ...
ascopubs.org

Deep-Learning Model for Real-Time Prediction of Recurrence in Early-Stage Non–Small Cell Lung Cancer: A Multimodal Approach (RADAR CARE Study)

Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...
GitHub

Multimodal deep learning for allergenic proteins prediction

Multimodal-AlgPro is an advanced deep learning framework designed to enhance allergen prediction by integrating multimodal data sources. By combining sequence, composition, physicochemical properties, ...