Video description: A comprehensive survey of deep learning approaches

G Rafiq, M Rafiq, GS Choi - Artificial Intelligence Review, 2023 - Springer
Video description refers to understanding visual content and transforming that acquired
understanding into automatic textual narration. It bridges the key AI fields of computer vision …

Video description: Datasets & evaluation metrics

M Rafiq, G Rafiq, GS Choi - IEEE Access, 2021 - ieeexplore.ieee.org
Rapid expansion and the novel phenomenon of deep learning have manifested a variety of
proposals and concerns in the area of video description, particularly in the recent past …

[HTML][HTML] Exploring Deep Learning Approaches for Video Captioning: A Comprehensive Review

AJ Yousif, MH Al-Jammas - e-Prime-Advances in Electrical Engineering …, 2023 - Elsevier
While humans can easily describe visual data at varying levels of detail, the same task
presents a significant challenge for machines. This challenge becomes even more complex …

Abnormal behavior recognition based on feature fusion C3D network

L Deng, R Fu, Q Sun, M Jiang, Z Li… - Journal of …, 2023 - spiedigitallibrary.org
The real-time detection and recognition ability of human action recognition in a video
surveillance system is a key problem in an intelligent surveillance system. Because the …

Radar and AIS Track Association Integrated Track and Scene Features through Deep Learning

B Jin, Y Tang, Z Zhang, Z Lian, B Wang - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
The navigation accuracy of the ship can be improved by associating the output tracks of
radar with that of the automatic identification system (AIS). The traditional association …

Optimization of the Electronic Nose Sensor Array for Asthma Detection Based on Genetic Algorithm

D Aulia, R Sarno, SC Hidayati, M Rivai - IEEE Access, 2023 - ieeexplore.ieee.org
The human body releases several gases and volatile organic compounds through exhaled
breath. This compound can be used as markers of lung disease, including asthma. An …

[PDF][PDF] 基于可拓展自注意力时空图卷积神经网络的用户轨迹识别模型

雷天亮, 吉立新, 王庚润, 刘树新, 巫岚 - 电子学报, 2024 - ejournal.org.cn
用户轨迹识别作为一项重要的时空数据挖掘任务, 广泛应用于基于位置的个性化服务推荐,
行程规划, 犯罪行为检测和目标跟踪等领域, 但依然面临预测精度不高的问题 …

Video spatio-temporal generative adversarial network for local action generation

X Liu, J Guo, Z Cui, L Liu, Y Yan… - Journal of Electronic …, 2023 - spiedigitallibrary.org
Generating action videos in future scenes based on static images can make computer vision
systems to be better applied for video understanding and intelligent decision-making …

Space Target Spin Motion Recognition Based on 3D Convolutional Networks

Y Zhang, X Feng, X Wei, C Zhu, C Huo… - Proceedings of the 2023 …, 2023 - dl.acm.org
As aerospace technology continues to progress, an increasing number of space targets are
being launched into orbit, putting pressure on limited space resources. Consequently …

I3D convolutional network algorithm with feature gating

J Yu, Y Lai, Y Liu - Proceedings of the 2023 6th International …, 2023 - dl.acm.org
In order to effectively solve the persistent problems of low accuracy and high computational
complexity in video retrieval, we propose a feature-controlled retrieval algorithm which …