Multi Stream

Multi-stream processing integrates data from multiple sources (e.g., images, audio, sensor data) to improve the accuracy and robustness of machine learning models. Current research focuses on developing efficient fusion architectures, such as multi-stream convolutional neural networks and transformer-based models, to effectively combine these diverse data streams for tasks like image registration, deepfake detection, and action recognition. This approach is proving valuable across various fields, enhancing the performance of applications ranging from medical diagnosis and disaster response to autonomous vehicle navigation and multimedia forensics.