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 ...
IEEE

Human Activity Recognition with FMCW Radar Using Few-Shot Learning on Raspberry Pi

Abstract: This study introduces a deep-learning framework for Human Activity Recognition (HAR) using spectrogram representations of FMCW radar data. Leveraging a publicly accessible dataset (DOI: ...
IEEE

Enhanced Visual-Semantic Interaction with Tailored Prompts for Pedestrian Attribute Recognition

Abstract: Pedestrian attribute recognition (PAR) seeks to predict multiple semantic attributes associated with a specific pedestrian. There are two types of approaches for PAR: unimodal framework and ...
IEEE

Multimodal Contrastive Learning for Cybersickness Recognition Using Brain Connectivity Graph Representation

Abstract: Cybersickness significantly impairs user comfort and immersion in virtual reality (VR). Effective identification of cybersickness leveraging physiological, visual, and motion data is a ...
IEEE

Neonatal Pain Speech Emotion Recognition Based on Multiscale Multilevel MAE Network

Abstract: Perception of neonatal pain is a critical indicator for early-life health assessment. However, in real-world clinical scenarios, it faces challenges such as poor objectivity and limited ...
IEEE

High-Performance CNN-Based Facial Recognition on the Yale Face Database

Abstract: Facial identification and detection have significantly risen due to deep learning techniques, especially Convolutional Neural Networks (CNNs), which perform better than traditional methods ...
IEEE

Special Convolution and Mask R-CNN: A New Method for Text Recognition on Cultural Relics

Abstract: This paper explores the use of artificial intelligence technology to restore and recognize blurred text on cultural relics. Traditional OCR technology has limitations in dealing with ...
IEEE

Performance Analysis of CNN-Based Spectrogram with Multiple Audio Feature Types for English Digit Recognition

Abstract: Audio feature selection and neural network architecture play crucial roles in speech recognition performance. This paper presents a comparative analysis of Artificial Neural Networks (ANNs) ...