4 accepted papers
Unmanned aerial vehicles (UAV)-based object detection with visible (RGB) and infrared (IR) images facilitates robust around-the-clock detection, driven by advancements in deep learning techniques and the availability of high-quality dataset. However, the existing dataset struggles to fully capture r…
Large Language Models (LLMs) have achieved remarkable success across many applications, with Mixture of Experts (MoE) models demonstrating great potential. Compared to traditional dense models, MoEs achieve better performance with less computation. Speculative decoding (SD) is a widely used techniqu…
Pre-trained Language Models in Natural Language Processing have become increasingly computationally expensive and memory demanding. The recently proposed computation-adaptive BERT models facilitate their deployment in practical applications. Training such a BERT model involves jointly optimizing sub…
Due to the limitation of image acquisition, hyperspectral remote sensing imagery is hard to reflect in both high spatial and spectral resolutions. Super-resolution (SR) is a technique which can improve the spatial resolution. Inspired by recent achievements in deep convolutional neural network (CNN)…