IEEE

Enhanced Student Learning Through Facial Emotion Recognition Using Normalized CNN and Deep Learning

Abstract: The identification of facial emotions through FER serves as a vital factor for both human-computer relationships and learning platforms designed for individual needs. The research presents ...
Biometric Update

STCon edges in among established facial recognition accuracy leaders in NIST 1:N

A handful of new facial recognition algorithms have been added to the NIST FRTE 1:N Identification this year, but most of the ...
IEEE

A Lightweight 1D-CNN for Emotion Recognition Based on EEG Multi Feature Fusion

Abstract: Emotion detection based on EEG is more objective and reliable compared to human actions and language. Recent advancements in deep learning technology have enabled the successful application ...
IEEE

Federated Edge Learning with Hybrid CNN-Transformers for Secure, High-Accuracy Face Recognition in Resource-Constrained IoT Systems

Abstract: Traditional face recognition systems struggle to balance accuracy, privacy, and computational efficiency in IoT environments. This work addresses these challenges by proposing a novel ...
IEEE

Adversarial Defense for Face Recognition via Identity-Embedded Features

Abstract: Face recognition systems based on deep neural networks remain susceptible to adversarial samples. Input reconstruction is a widely adopted defense due to its independence from the target ...
CNN

‘I’m simply not making any money’: Iran war is squeezing US small businesses

John Andrews, a South Carolina-based chef who runs a meal delivery service, estimates he drives over 100 miles every week to deliver fresh home-cooked meals to his clients. “The economy is killing me ...
Biometric Companies

Iris ID debuts in NIST FRTE 1:1, ROC impresses with updated algorithm

The latest edition of NIST’s ongoing report series evaluating biometric face verification accuracy includes the debut of algorithms from Iris ID and Vietnam-based FPT Telecom JSC, along with new ...
IEEE

Optimizing Hybrid Classification Using 1D-CNN and LSTM for EEG-Based Emotion Recognition

Abstract: This research aims to enhance the ability of computers to classify emotional states from brain signals using EEG data. Emotions are complex mental states that can significantly affect a ...
IEEE

Evaluation of Deep Learning and Machine Learning Algorithms for Facial Emotion Recognition

Abstract: Facial Emotion Recognition is a crucial aspect of human-computer interaction, with applications in healthcare, security, psychology, and artificial intelligence. This research presents a ...
IEEE

A Verified Synergistic Deep Learning Framework for Copyrighted Character Recognition Using CNN and Transformer Integration

Abstract: In this paper, we proposed a novel deep learning framework, the Synergistic Deep Learning Model, for recognizing copyrighted characters with heightened accuracy and minimized overfitting.
IEEE

Deep Learning Approaches to Babylonian Numeral Recognition: A CNN-SVM Hybrid Model

Abstract: This paper presents a novel deep learning framework for classifying Babylonian numerals by integrating Convolutional Neural Networks (CNNs) with a hybrid CNN-SVM model. The core ...