Deep learning
Multi-layer neural networks (e.g. CNNs, LSTMs) that learn representations directly from data.
12 papers carry this themeView in grid →
In these papers
- 01An empirical study of AI techniques in mobile applications ✩Haoye Tian b, Zhijie Wang c et al. · 2024Deep-learning technologies in AI-driven mobile apps.
- 02Classifying Emotional States through EEG-Derived Spectrograms2024Classifies emotion from EEG-derived spectrogram images.
- 03Harnessing AI potential in E-Commerce: improving user engagement and sales through deep learning-based product recommendationsZhang · 2024DL-based recommendation reshaping e-commerce.
- 04Next-Gen Human-Computer Interaction: A HybridRavindra Changal · 2024Fuses LSTM and CNN for next-gen HCI.
- 05Toward an Interactive Reading Experience: Deep Learning Insights and Visual Narratives of Engagement and EmotionJayasankar Santhosh, Akshay Palimar Pai et al. · 2024Deep-learning insights into the reading experience.
- 06A Novel User Emotional Interaction Design Model Using Long and Short-Term Memory Networks and Deep Learning2021Uses LSTM networks with a self-attention mechanism for the model.
- 07Deep Learning for Emotion Driven User ExperiencesCarmen Bisogni, Lucia Cascone et al. · 2021Deep learning for emotion-driven user experiences.
- 08Recommendation Engines: Traditional vs Deep Learning ApproachesAniket Dhawa, Suranjana Sarkar et al. · 2021Compares traditional and deep-learning recommenders.
- 09Deep Learning UI Design Patterns of Mobile AppsPhong Minh Vu, Hung Viet Pham et al. · 2018Deep learning to (semi-)automate mobile UI design tasks.
- 10Deep Neural Networks for YouTube RecommendationsPaul Covington, Jay Adams et al. · 2016Deep neural networks power candidate generation and ranking.
- 11ImageNet Classification with Deep Convolutional Neural NetworksAlex Krizhevsky · 2010The AlexNet deep CNN that launched modern deep learning.
- 12Improving Language Understanding by Generative Pre-TrainingAlec RadforGenerative pre-training on large unlabeled corpora.