AI and Machine Learning

Track 13: Deep Learning & Neural Computing

Deep Learning focuses on advanced neural network architectures capable of learning complex patterns and representations from large-scale datasets. This track explores CNNs, RNNs, LSTMs, Transformers, and emerging neural computing architectures. It addresses deep learning training strategies, optimization, transfer learning, representation learning, and computational efficiency. Researchers can present innovative approaches for improving model accuracy, scalability, robustness, and performance. The track highlights the growing role of deep learning and neural computing in intelligent, automated, and data-driven applications.

• Advanced Deep Neural Network Architectures

• CNNs, RNNs, LSTMs and Transformers

• Neural Architecture Search and Model Compression

• Emerging Neural Computing Technologies