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Jun-Hwa Kim and Chee Sun Won
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Nils Hütten, Miguel Alves Gomes, Florian Hölken, Karlo Andricevic, Richard Meyes and Tobias Meisen
Quality assessment in industrial applications is often carried out through visual inspection, usually performed or supported by human domain experts. However, the manual visual inspection of processes and products is error-prone and expensive. It is ther...
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Qian Zhou, Hua Zou and Huanhuan Wu
Vision Transformers (ViTs) have shown their superiority in various visual tasks for the capability of self-attention mechanisms to model long-range dependencies. Some recent works try to reduce the high cost of vision transformers by limiting the self-at...
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Hechen Yang, Xin Zhao, Tao Jiang, Jinghua Zhang, Peng Zhao, Ao Chen, Marcin Grzegorzek, Shouliang Qi, Yueyang Teng and Chen Li
Currently, the field of transparent image analysis has gradually become a hot topic. However, traditional analysis methods are accompanied by large amounts of carbon emissions, and consumes significant manpower and material resources. The continuous deve...
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Yicheng Luo, Yajing Xu, Si Li, Qifeng Qian and Bo Xiao
Convolutional neural networks have achieved great success in analyzing potential features inside tropical cyclones (TCs) using satellite images for intensity estimation. However, due to the high similarity of visual features in TC images, it is still a c...
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Oscar Ondeng, Heywood Ouma and Peter Akuon
Visual understanding is a research area that bridges the gap between computer vision and natural language processing. Image captioning is a visual understanding task in which natural language descriptions of images are automatically generated using visio...
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Abeer Abdulaziz AlArfaj and Hanan Ahmed Hosni Mahmoud
Moving object tracking techniques using machine and deep learning require large datasets for neural model training. New strategies need to be invented that utilize smaller data training sizes to realize the impact of large-sized datasets. However, curren...
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Hongye Liu and Xiai Chen
Person re-identification aims to identify the same pedestrians captured by various cameras from different viewpoints in multiple scenarios. Occlusion is the toughest problem for practical applications. In video-based ReID tasks, motion information can be...
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Mingyang Yu, Haiqing Xu, Fangliang Zhou, Shuai Xu and Hongling Yin
Accurate and efficient classification maps of urban functional zones (UFZs) are crucial to urban planning, management, and decision making. Due to the complex socioeconomic UFZ properties, it is increasingly challenging to identify urban functional zones...
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Zifan Rong, Xuesong Jiang, Linfeng Huang and Hongping Zhou
Pan-sharpening aims to create high-resolution spectrum images by fusing low-resolution hyperspectral (HS) images with high-resolution panchromatic (PAN) images. Inspired by the Swin transformer used in image classification tasks, this research constructs...
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Yundong Li, Xiaokun Wei and Hanlu Fan
Monocular depth estimation (MDE), as one of the fundamental tasks of computer vision, plays important roles in downstream applications such as virtual reality, 3D reconstruction, and robotic navigation. Convolutional neural networks (CNN)-based methods g...
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Zhongchang Ye, Xin Ye and Zhonghua Zhao
Intelligent video surveillance (IVS) technology is widely used in various security systems. However, quality degradation in surveillance images (SIs) may affect its performance on vision-based tasks, leading to the difficulties in the IVS system extracti...
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Xulong Yu, Qiancheng Yu, Qunyue Mu, Zhiyong Hu and Jincai Xie
Traditional manual visual detection methods are inefficient, subjective, and costly, making them prone to false and missed detections. Deep-learning-based defect detection identifies the types of defects and pinpoints their locations. By employing this a...
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Tomotaka Fukuoka and Makoto Fujiu
In Japan, bridges are inspected via close visual examinations every five years. However, these inspections are labor intensive, and a shortage of engineers and budget constraints will restrict such inspections in the future. In recent years, efforts have...
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Hongmei Zhang and Shuiqing Wang
The analysis of thin sections for lithology identification is a staple technique in geology. Although recent strides in deep learning have catalyzed the development of models for thin section recognition leveraging varied deep neural networks, there rema...
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Yongkang Wang, Jundong Zhang, Jinting Zhu, Yuequn Ge and Guanyu Zhai
In the intelligent engine room, the visual perception of ship engine room equipment is the premise of defect identification and the replacement of manual operation. This paper improves YOLOv5 for the problems of mutual occlusion of cabin equipment, an un...
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Yi Liang, Turdi Tohti and Askar Hamdulla
In the existing false information detection methods, the quality of the extracted single-modality features is low, the information between different modalities cannot be fully fused, and the original information will be lost when the information of diffe...
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Teerapong Panboonyuen, Sittinun Thongbai, Weerachai Wongweeranimit, Phisan Santitamnont, Kittiwan Suphan and Chaiyut Charoenphon
Due to the various sizes of each object, such as kilometer stones, detection is still a challenge, and it directly impacts the accuracy of these object counts. Transformers have demonstrated impressive results in various natural language processing (NLP)...
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