Vol 3, No 1 (2023): Advances in Deep Learning Techniques
Issue Description
Welcome to Volume 3, Issue 1 of Advances in Deep Learning Techniques, where we continue our journey into the forefront of deep learning research. In this edition, we present two pioneering papers that delve into critical aspects of deep learning innovation. "Capsule Networks - Advancements and Implementations" explores the latest advancements in capsule networks and their implementations, aimed at improving robustness in image recognition tasks. Concurrently, "Gated Recurrent Units - Enhancements and Applications" investigates enhancements to Gated Recurrent Unit (GRU) architectures and their applications in sequential modeling tasks. Join us as we unravel the complexities of deep learning, paving the way for transformative breakthroughs in artificial intelligence and machine learning.