For years, the YOLO series has been the de facto industry-level standard for efficient object
detection. The YOLO community has prospered overwhelmingly to enrich its use in a …

Knowledge distillation, in which a student model is trained to mimic a teacher model, has
been proved as an effective technique for model compression and model accuracy boosting …

Abstract Unlike the conventional Knowledge Distillation (KD), Self-KD allows a network to
learn knowledge from itself without any guidance from extra networks. This paper proposes …

The success of deep learning is usually accompanied by the growth in neural network
depth. However, the traditional training method only supervises the neural network at its last …

Knowledge distillation, which aims to transfer the knowledge learned by a cumbersome
teacher model to a lightweight student model, has become one of the most popular and …

Deep neural networks have achieved remarkable performance for artificial intelligence
tasks. The success behind intelligent systems often relies on large-scale models with high …

Reinforced concrete bridge substructures are one of the most important road components,
requiring routine maintenance for road safety. These structures initially require visual …

In recent years, computer-aided automatic polyp segmentation and neoplasm detection
have been an emerging topic in medical image analysis, providing valuable support to …

Security-sensitive applications that rely on Deep Neural Networks (DNNs) are vulnerable to
small perturbations that are crafted to generate Adversarial Examples. The (AEs) are …

The performance of computer vision models are susceptible to unexpected changes in input
images caused by sensor errors or extreme imaging environments, known as common …