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Haleem Farman, Moustafa M. Nasralla, Sohaib Bin Altaf Khattak and Bilal Jan
Fire detection employing vision sensors has drawn significant attention within the computer vision community, primarily due to its practicality and utility. Previous research predominantly relied on basic color features, a methodology that has since been...
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Alyaa Amer, Tryphon Lambrou and Xujiong Ye
The advanced development of deep learning methods has recently made significant improvements in medical image segmentation. Encoder?decoder networks, such as U-Net, have addressed some of the challenges in medical image segmentation with an outstanding p...
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Md. Khaliluzzaman, Md. Abu Bakar Siddiq Sayem, Lutful KaderMisbah
Pág. 357 - 376
Human Activity Recognition (HAR), a vast area of a computer vision research, has gained standings in recent years due to its applications in various fields. As human activity has diversification in action, interaction, and it embraces a large amount of d...
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Seol-Hyun Noh
Convolutional neural networks (CNNs) are widely used among the various deep learning techniques available because of their superior performance in the fields of computer vision and natural language processing. CNNs can effectively extract the locality an...
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Uche Onyekpe, Vasile Palade, Stratis Kanarachos and Stavros-Richard G. Christopoulos
Recurrent Neural Networks (RNNs) are known for their ability to learn relationships within temporal sequences. Gated Recurrent Unit (GRU) networks have found use in challenging time-dependent applications such as Natural Language Processing (NLP), financ...
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Yong Fang, Shaoshuai Yang, Bin Zhao and Cheng Huang
With the propagation of cyberbullying in social networks as a trending subject, cyberbullying detection has become a social problem that researchers are concerned about. Developing intelligent models and systems helps detect cyberbullying automatically. ...
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Jing Zheng, Ziren Gao, Jingsong Ma, Jie Shen and Kang Zhang
The selection of road networks is very important for cartographic generalization. Traditional artificial intelligence methods have improved selection efficiency but cannot fully extract the spatial features of road networks. However, current selection me...
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Wei Huang, Jingjing Feng, Hua Wang and Le Sun
In this paper, we propose a new architecture of densely connected convolutional networks for pan-sharpening (DCCNP). Since the traditional convolution neural network (CNN) has difficulty handling the lack of a training sample set in the field of remote s...
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Fengzhen Sun, Shaojie Li, Shaohua Wang, Qingjun Liu and Lixin Zhou
Predicting the futures from previous spatiotemporal data remains a challenging topic. There have been many previous works on predictive learning. However, mainstream models suffer from huge memory usage or the gradient vanishing problem. Enlightened by t...
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Inkyu Choi, Soo Hyun Bae and Nam Soo Kim
Audio event detection (AED) is a task of recognizing the types of audio events in an audio stream and estimating their temporal positions. AED is typically based on fully supervised approaches, requiring strong labels including both the presence and temp...
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