<p class="jove_content">This study built a deep learning model using EEG signals and music familiarity to predict music genre preference. Data were collected with a low&#8209;cost Muse S device and analyzed using a CNN+RNN and an EEGNet model. Familiarity significantly improved accuracy, reaching up to 99%, showing its substantial value in preference prediction.</p>

construction-music-genre-preference-recognition-model-based-on-deep

Construction of a Music Genre Preference Recognition Model Based on Deep Learning

With the increasing prevalence of mental health issues, music therapy has gained attention as a non-pharmacological intervention, and deep learning ...

<p class="jove_content">To address challenges like occlusion and lighting changes in automated warehouses, this paper introduces an improved Single-stage Regression Architecture for cigarette box brand detection. By integrating adaptive downsampling, an inverted efficient multi-scale attention mechanism, and a dynamic detection head, the proposed model achieves accurate, real-time Intelligent stocktaking.</p>

real-time-object-detection-model-for-cigarette-brand-identification

Real-time Object Detection Model for Cigarette Brand Identification Based on an Improved Single-stage Regression Architecture

Visual recognition for automated cigarette inventory faces significant hurdles, including illumination changes, diverse box dimensions, and partial ...

Institution - Quzhou University

Articles Published in JoVE