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Danilo Pau, Andrea Pisani and Antonio Candelieri
In the context of TinyML, many research efforts have been devoted to designing forward topologies to support On-Device Learning. Reaching this target would bring numerous advantages, including reductions in latency and computational complexity, stronger ...
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Hassen Louati, Ali Louati, Rahma Lahyani, Elham Kariri and Abdullah Albanyan
Responding to the critical health crisis triggered by respiratory illnesses, notably COVID-19, this study introduces an innovative and resource-conscious methodology for analyzing chest X-ray images. We unveil a cutting-edge technique that marries neural...
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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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Boyu Xie, Qi Su, Beilun Tang, Yan Li, Zhengwu Yang, Jiaoyang Wang, Chenxi Wang, Jingxian Lin and Lin Li
With the advancement in modern agricultural technologies, ensuring crop health and enhancing yield have become paramount. This study aims to address potential shortcomings in the existing chili disease detection methods, particularly the absence of optim...
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Qianlong Jin, Yu Tian, Weicong Zhan, Qiming Sang, Jiancheng Yu and Xiaohui Wang
Efficiently predicting high-resolution and accurate flow fields through networked autonomous marine vehicles (AMVs) is crucial for diverse applications. Nonetheless, a research gap exists in the seamless integration of data-driven flow modeling, real-tim...
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Stefan Hensel, Marin B. Marinov and Raphael Panter
In recent years, the advancement of micro-aerial vehicles has been rapid, leading to their widespread utilization across various domains due to their adaptability and efficiency. This research paper focuses on the development of a camera-based tracking s...
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Chunxian Wang, Xiaoxing Wang, Yiwen Wang, Shengchao Hu, Hongyang Chen, Xuehai Gu, Junchi Yan and Tao He
Neural architecture search (NAS) is a popular branch of automatic machine learning (AutoML), which aims to search for efficient network structures. Many prior works have explored a wide range of search algorithms for classification tasks, and have achiev...
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Sana Shams and Muhammad Aslam
Detecting the communicative intent behind user queries is critically required by search engines to understand a user?s search goal and retrieve the desired results. Due to increased web searching in local languages, there is an emerging need to support t...
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Joseph Isabona, Agbotiname Lucky Imoize, Stephen Ojo, Olukayode Karunwi, Yongsung Kim, Cheng-Chi Lee and Chun-Ta Li
Modern cellular communication networks are already being perturbed by large and steadily increasing mobile subscribers in high demand for better service quality. To constantly and reliably deploy and optimally manage such mobile cellular networks, the ra...
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Yurika Permanasari, Budi Nurani Ruchjana, Setiawan Hadi and Juli Rejito
Object identification is a part of the field of computer science, namely, image processing, whose research continues to innovate. Object identification describes an object based on the main characteristics of the object. Many research innovations related...
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