Deep Learning
Deep learning, a subfield of machine learning, focuses on training artificial neural networks with multiple layers to extract complex patterns from data. Current research emphasizes improving model robustness against noisy or adversarial inputs, exploring efficient architectures like Vision Transformers and convolutional LSTMs for various tasks (e.g., image classification, time series forecasting), and integrating physics-informed approaches for enhanced interpretability and reliability. These advancements are significantly impacting diverse fields, from automated industrial inspection and medical image analysis to improved weather forecasting and more efficient content moderation systems.
3874papers
Papers - Page 30
December 6, 2024
December 5, 2024
Physics-informed Deep Learning for Muscle Force Prediction with Unlabeled sEMG Signals
Methodology for Online Estimation of Rheological Parameters in Polymer Melts Using Deep Learning and Microfluidics
DeepFEA: Deep Learning for Prediction of Transient Finite Element Analysis Solutions
Automated Medical Report Generation for ECG Data: Bridging Medical Text and Signal Processing with Deep Learning
Benchmarking and Enhancing Surgical Phase Recognition Models for Robotic-Assisted Esophagectomy
Deep Learning and Hybrid Approaches for Dynamic Scene Analysis, Object Detection and Motion Tracking
Deep Learning Modeling Method for RF Devices Based on Uniform Noise Training Set
Using SlowFast Networks for Near-Miss Incident Analysis in Dashcam Videos
Dual-Branch Subpixel-Guided Network for Hyperspectral Image Classification
December 4, 2024
Deep Learning for Sea Surface Temperature Reconstruction under Cloud Occlusion
Deep Learning in Single-Cell and Spatial Transcriptomics Data Analysis: Advances and Challenges from a Data Science Perspective
FlashAttention on a Napkin: A Diagrammatic Approach to Deep Learning IO-Awareness
Few-Shot Learning with Adaptive Weight Masking in Conditional GANs
December 3, 2024
An ADHD Diagnostic Interface Based on EEG Spectrograms and Deep Learning Techniques
Medical Multimodal Foundation Models in Clinical Diagnosis and Treatment: Applications, Challenges, and Future Directions
OMENN: One Matrix to Explain Neural Networks
Deep Learning, Machine Learning, Advancing Big Data Analytics and Management