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Md Firoz Kabir Innovative AI Research Aims to Improve Cancer and Cardiac Outcomes Through Earlier and More Accurate Diagnosis

Md Firoz Kabir, a PhD researcher in Information Technology, is emerging as a leading voice in artificial intelligence-driven ...
Scientific Research Publishing

Geo-Refined Point Transformer: Coordinate-Aware Excitation and Positional Upsampling for 3D Scene Segmentation ()

The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...
EurekAlert!

Research Article | A transformer-based multi-feature fusion method for detecting traffic events using Twitter data

A new study published in Big Earth Data demonstrates that integrating Twitter data with deep learning techniques can ...
Security Boulevard

NDSS 2025 – Probe-Me-Not: Protecting Pre-trained Encoders From Malicious Probing

Ruyi Ding (Northeastern University), Tong Zhou (Northeastern University), Lili Su (Northeastern University), Aidong Adam Ding (Northeastern University), Xiaolin Xu (Northeastern University), Yunsi Fei ...
eLife

Separating selection from mutation in antibody language models

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
GitHub

Deep Reinforcement Learning for Service Function Chain Placement with Graph Attention and Transformer Encoder

This repository contains the implementation of the paper of paper Deep Reinforcement Learning for Service Function Chain Placement with Graph Attention and Transformer Encoder. In this paper, we ...
IEEE

SleepHybridNet: A Lightweight Hybrid CNN-Transformer Model for Enhanced N1 Sleep Staging From Single-Channel EEG

Abstract: This study introduces SleepHybridNet, a lightweight hybrid CNN-Transformer model designed to enhance the classification of non-rapid eye movement stage 1 (N1) sleep using single-channel ...
Frontiers

Meta analysis of the diagnostic efficacy of transformer-based multimodal fusion deep learning models in early Alzheimer’s disease

Department of Neurology, Xianyang Hospital of Yan’an University, Xianyang, China Introduction: This study aims to systematically evaluate the diagnostic efficacy of Transformer-based multimodal fusion ...
Frontiers

Oral squamous cell carcinoma grading classification using deep transformer encoder assisted dilated convolution with global attention

In recent years, Oral Squamous Cell Carcinoma (OSCC) has been a common tumor in the orofacial region, affecting areas such as the teeth, jaw, and temporomandibular joint. OSCC is classified into three ...
marktechpost

A Coding Implementation to Build a Transformer-Based Regression Language Model to Predict Continuous Values from Text

We will build a Regression Language Model (RLM), a model that predicts continuous numerical values directly from text sequences in this coding implementation. Instead of classifying or generating text ...
IEEE

Resilient 3D Indoor Localization Using a Masked Transformer Encoder with Multi-band CSI Fingerprints

Abstract: Integrating dense channel fingerprints into deep learning (DL) becomes a promising way to realize precise three-dimensional (3D) indoor localization. However, most existing methods are ...