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Ruicheng Gao, Zhancai Dong, Yuqi Wang, Zhuowen Cui, Muyang Ye, Bowen Dong, Yuchun Lu, Xuaner Wang, Yihong Song and Shuo Yan
In this study, a deep-learning-based intelligent detection model was designed and implemented to rapidly detect cotton pests and diseases. The model integrates cutting-edge Transformer technology and knowledge graphs, effectively enhancing pest and disea...
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Varsha S. Lalapura, Veerender Reddy Bhimavarapu, J. Amudha and Hariram Selvamurugan Satheesh
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning algorithms. Complex tasks like speech recognition, machine translation, sentiment classification, weather prediction, etc., are now performed by well-trained RNNs. Local o...
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Hao Liu, Bo Yang and Zhiwen Yu
Multimodal sarcasm detection is a developing research field in social Internet of Things, which is the foundation of artificial intelligence and human psychology research. Sarcastic comments issued on social media often imply people?s real attitudes towa...
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Omar Banimelhem and Fidaa Al-Quran
In this paper, an adaptive path construction approach for Mobile Sink (MS) in wireless sensor networks (WSNs) for data gathering has been proposed. The path is constructed based on selecting Rendezvous Points (RPs) in the sensing field where the MS stops...
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Jizhong Deng, Chang Yang, Kanghua Huang, Luocheng Lei, Jiahang Ye, Wen Zeng, Jianling Zhang, Yubin Lan and Yali Zhang
The realization that mobile phones can detect rice diseases and insect pests not only solves the problems of low efficiency and poor accuracy from manually detection and reporting, but it also helps farmers detect and control them in the field in a timel...
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Rio Arifando, Shinji Eto and Chikamune Wada
Object detection is crucial for individuals with visual impairment, especially when waiting for a bus. In this study, we propose a lightweight and highly accurate bus detection model based on an improved version of the YOLOv5 model. We propose integratin...
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Michail Niarchos, Marina Eirini Stamatiadou, Charalampos Dimoulas, Andreas Veglis and Andreas Symeonidis
Nowadays, news coverage implies the existence of video footage and sound, from which arises the need for fast reflexes by media organizations. Social media and mobile journalists assist in fulfilling this requirement, but quick on-site presence is not al...
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Dweepna Garg, Priyanka Jain, Ketan Kotecha, Parth Goel and Vijayakumar Varadarajan
In recent years, face detection has achieved considerable attention in the field of computer vision using traditional machine learning techniques and deep learning techniques. Deep learning is used to build the most recent and powerful face detection alg...
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Zhaohui Huang and Vasilis Friderikos
Mobile Augmented Reality (MAR) applications demand significant communication, computing and caching resources to support an efficient amalgamation of augmented reality objects (AROs) with the physical world in multiple video view streams. In this paper, ...
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Rachel M. Billings and Alan J. Michaels
While a variety of image processing studies have been performed to quantify the potential performance of neural network-based models using high-quality still images, relatively few studies seek to apply those models to a real-time operational context. Th...
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