Question answering, serving as one of important tasks in natural language processing,
enables machines to understand questions in natural language and answer the questions …

With the rapid development of the times, people have entered the era of intelligence, and the
application of big data algorithms is becoming increasingly widespread. The satisfaction of …

In the wake of developments in remote sensing, the application of target detection of remote
sensing is of increasing interest. Unfortunately, unlike natural image processing, remote …

Currently, the integration of the supply chain and blockchain is promising, as blockchain
successfully eliminates the bullwhip effect in the supply chain. Generally, concurrent …

Sentence semantic matching (SSM) always plays a critical role in natural language
processing. Measuring the intrinsic semantic similarity among sentences is very challenging …

In this paper, a spectral-spatial convolution neural network with Siamese architecture
(SSCNN-S) for hyperspectral image (HSI) change detection (CD) is proposed. First, tensors …

In recent years, text matching has gained increasing research focus and shown great
improvements. However, due to the long-distance dependency and polysemy, existing text …

Currently, the generative adversarial network (GAN), with complex training processes in the
physical machine (PM), has achieved great priority in image generation, audio conversion …

Accurate high spatial resolution snow depth map** in arid and semi-arid regions is of
great importance for snow disaster assessment and hydrological modeling. However, due to …

Recently, deep learning methods based on the combination of spatial and spectral features
have been successfully applied in hyperspectral image (HSI) classification. To improve the …