Since the introduction of the Vision Transformer (ViT), researchers have sought to make ViTs
more efficient by removing redundant information in the processed tokens. While different …

Cracks are an essential indicator of infrastructure degradation, and achieving high-
precision, pixel-level crack segmentation is a common goal for artificial intelligence (AI) …

With the continuous development of urbanization, the service life of sewer pipes is gradually
approaching a critical threshold. Defects within pipe networks can significantly affect the …

In recent studies, convolutional neural networks (CNNs) are mostly used as dynamic
techniques for visualization-based malware classification and detection. Though vision …

Rapid urbanization and population growth in recent decades have placed significant
pressure on urban cities to rely heavily on underground infrastructure, such as sewers and …

Diseases in agricultural products cause significant decrease on harvest efficiency and
economic values of the products, early detection of diseases can prevent this loss. The …

Abstract We present Agglomerative Token Clustering (ATC), a novel token merging method
that consistently outperforms previous token merging and pruning methods across image …

Sewer systems are critical to smart city infrastructure, but conventional pipeline inspection
methods cause high costs and inefficiency. This paper presents a real-time detection …

We introduce PRANCE, a Vision Transformer compression framework that jointly optimizes
the activated channels and reduces tokens, based on the characteristics of inputs …

Cracks provide an essential indicator of infrastructure performance degradation, and
achieving high-precision pixel-level crack segmentation is an issue of concern. Unlike the …