High Performing

High-performing neural networks are a central focus in current artificial intelligence research, aiming to improve efficiency and accuracy across various applications. Research efforts concentrate on novel architectures, such as spiking neural networks (SNNs) and optimized convolutional neural networks (CNNs), and advanced training techniques like evolutionary algorithms and training-free conversion methods to reduce computational costs. These advancements are crucial for deploying deep learning models on resource-constrained devices and improving performance in tasks ranging from image classification to object detection, impacting both scientific understanding of neural networks and practical applications in diverse fields. The development of efficient neural architecture search (NAS) methods further accelerates the discovery of high-performing architectures tailored to specific hardware and task constraints.