Efficiently modeling sequences with infinite context length has been a long-standing
problem. Past works suffer from either the quadratic computation complexity or the limited …

Image segmentation is consistently an important task for computer vision and the analysis of
medical images. The analysis and diagnosis of histopathology images by using efficient …

The proliferation of edge devices driven by advancements in Internet of Things (IoT)
technology has intensified the challenge of achieving high-precision small target detection …

Background and objective Atrial fibrillation (AF) is one of the most frequent asymptomatic
arrhythmias associated with significant morbidity and mortality. Identifying the susceptibility …

Breast cancer is defined as abnormal cellular proliferation in the breast. The most common
kind of cancer that affects the breast and causes mortality in women is invasive ductal …

One of the most challenging problems faced by ecologists and other biological researchers
today is to analyze the massive amounts of data being collected by advanced monitoring …

Quantization plays a crucial role in efficiently deploying deep learning models on resources
constraint devices. Post-training quantization does not require either access to the original …

Road extraction from images captured via remote sensing is a pivotal task across multiple
domains, encompassing urban planning and intelligent transportation systems. In the realm …

Deep convolutional neural networks have been proven successful in multiple benchmark
challenges in recent years. However, the performance improvements are heavily reliant on …

Visual Dialog is a multi-modal task involving both computer vision and dialog systems. The
goal is to answer multiple questions in conversation style, given an image as the context …