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Moiz Hassan, Kandasamy Illanko and Xavier N. Fernando
Single Image Super Resolution (SSIR) is an intriguing research topic in computer vision where the goal is to create high-resolution images from low-resolution ones using innovative techniques. SSIR has numerous applications in fields such as medical/sate...
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Nyo Me Htun, Toshiaki Owari, Satoshi Tsuyuki and Takuya Hiroshima
High-value timber species with economic and ecological importance are usually distributed at very low densities, such that accurate knowledge of the location of these trees within a forest is critical for forest management practices. Recent technological...
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Mohamad Abou Ali, Fadi Dornaika and Ignacio Arganda-Carreras
Artificial intelligence (AI) has emerged as a cutting-edge tool, simultaneously accelerating, securing, and enhancing the diagnosis and treatment of patients. An exemplification of this capability is evident in the analysis of peripheral blood smears (PB...
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Mohamad Abou Ali, Fadi Dornaika and Ignacio Arganda-Carreras
Deep learning (DL) has made significant advances in computer vision with the advent of vision transformers (ViTs). Unlike convolutional neural networks (CNNs), ViTs use self-attention to extract both local and global features from image data, and then ap...
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Xiaoyu Han, Chenyu Li, Zifan Wang and Guohua Liu
Neural architecture search (NAS) has shown great potential in discovering powerful and flexible network models, becoming an important branch of automatic machine learning (AutoML). Although search methods based on reinforcement learning and evolutionary ...
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Raluca Chitic, Ali Osman Topal and Franck Leprévost
Recently, convolutional neural networks (CNNs) have become the main drivers in many image recognition applications. However, they are vulnerable to adversarial attacks, which can lead to disastrous consequences. This paper introduces ShuffleDetect as a n...
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Jingying Zhang and Tengfei Bao
Crack detection is an important component of dam safety monitoring. Detection methods based on deep convolutional neural networks (DCNNs) are widely used for their high efficiency and safety. Most existing DCNNs with high accuracy are too complex for use...
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Huoxiang Yang, Yongsheng Liang, Wei Liu and Fanyang Meng
Due to the effective guidance of prior information, feature map-based pruning methods have emerged as promising techniques for model compression. In the previous works, the undifferentiated treatment of all information on feature maps amplifies the negat...
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Giuseppe Ciaburro, Sankar Padmanabhan, Yassine Maleh and Virginia Puyana-Romero
The modern conception of industrial production recognizes the increasingly crucial role of maintenance. Currently, maintenance is thought of as a service that aims to maintain the efficiency of equipment and systems while also taking quality, energy effi...
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Erica Perseghin and Gian Luca Foresti
This paper presents a novel low-cost integrated system prototype, called School Violence Detection system (SVD), based on a 2D Convolutional Neural Network (CNN). It is used for classifying and identifying automatically violent actions in educational env...
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