Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Pan, Shirui"'
The vision-and-language navigation (VLN) task necessitates an agent to perceive the surroundings, follow natural language instructions, and act in photo-realistic unseen environments. Most of the existing methods employ the entire image or object fea
Externí odkaz:
http://arxiv.org/abs/2406.01256
A key objective in field of artificial intelligence is to develop cognitive models that can exhibit human-like intellectual capabilities. One promising approach to achieving this is through neural-symbolic systems, which combine the strengths of deep
Externí odkaz:
http://arxiv.org/abs/2309.08931
Automatic generation of ophthalmic reports using data-driven neural networks has great potential in clinical practice. When writing a report, ophthalmologists make inferences with prior clinical knowledge. This knowledge has been neglected in prior m
Externí odkaz:
http://arxiv.org/abs/2206.01988
Face recognition has been greatly facilitated by the development of deep neural networks (DNNs) and has been widely applied to many safety-critical applications. However, recent studies have shown that DNNs are very vulnerable to adversarial examples
Externí odkaz:
http://arxiv.org/abs/2109.09320
Nowadays, deep learning methods, especially the Graph Convolutional Network (GCN), have shown impressive performance in hyperspectral image (HSI) classification. However, the current GCN-based methods treat graph construction and image classification
Externí odkaz:
http://arxiv.org/abs/2009.09196
Few-shot learning is currently enjoying a considerable resurgence of interest, aided by the recent advance of deep learning. Contemporary approaches based on weight-generation scheme delivers a straightforward and flexible solution to the problem. Ho
Externí odkaz:
http://arxiv.org/abs/1911.12476
In hyperspectral image (HSI) classification, spatial context has demonstrated its significance in achieving promising performance. However, conventional spatial context-based methods simply assume that spatially neighboring pixels should correspond t
Externí odkaz:
http://arxiv.org/abs/1909.11953
Label embedding plays an important role in many real-world applications. To enhance the label relatedness captured by the embeddings, multiple contexts can be adopted. However, these contexts are heterogeneous and often partially observed in practica
Externí odkaz:
http://arxiv.org/abs/1805.01199