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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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Sergiu Cosmin Nistor, Tudor Alexandru Ileni and Adrian Sergiu Darabant
Machine learning is a branch of artificial intelligence that has gained a lot of traction in the last years due to advances in deep neural networks. These algorithms can be used to process large quantities of data, which would be impossible to handle man...
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Kang-moon Park, Donghoon Shin and Sung-do Chi
Neural Network Structure Learning is expected to overcome difficulty of constructing a neural network structure.
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Oluwatoyin Joy Omole, Renata Lopes Rosa, Muhammad Saadi and Demóstenes Zegarra Rodriguez
Soybean is a critical agricultural commodity, serving as a vital source of protein and vegetable oil, and contributing significantly to the economies of producing nations. However, soybean yields are frequently compromised by disease and pest infestation...
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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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Zhirui Luo, Qingqing Li, Ruobin Qi and Jun Zheng
Background: Accurately identifying the socio-demographic information of customers is crucial for utilities. It enables them to efficiently deliver personalized energy services and manage distribution networks. In recent years, machine learning-based data...
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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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Yannick Robin, Johannes Amann, Tobias Baur, Payman Goodarzi, Caroline Schultealbert, Tizian Schneider and Andreas Schütze
With air quality being one target in the sustainable development goals set by the United Nations, accurate monitoring also of indoor air quality is more important than ever. Chemiresistive gas sensors are an inexpensive and promising solution for the mon...
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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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Euna Lee, Myungwoo Nam and Hongchul Lee
Since demand is influenced by a wide variety of causes, it is necessary to decompose the explanatory variables into different levels, extract their relationships effectively, and reflect them in the forecast. In particular, this contextual information ca...
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Ricardo Landa, David Tovias-Alanis and Gregorio Toscano
This work proposes the use of a micro genetic algorithm to optimize the architecture of fully connected layers in convolutional neural networks, with the aim of reducing model complexity without sacrificing performance. Our approach applies the paradigm ...
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Bujin Shi, Xinbo Zhou, Peilin Li, Wenyu Ma and Nan Pan
With the rapid growth of power demand and the advancement of new power system intelligence, smart energy measurement system data quality and security are also facing the influence of diversified factors. To solve the series of problems such as low data p...
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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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Zhou Lei, Kangkang Yang, Kai Jiang and Shengbo Chen
Person re-Identification(Re-ID) based on deep convolutional neural networks (CNNs) achieves remarkable success with its fast speed. However, prevailing Re-ID models are usually built upon backbones that manually design for classification. In order to aut...
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Pedro M. R. Bento, Jose A. N. Pombo, Maria R. A. Calado and Silvio J. P. S. Mariano
Short-Term Load Forecasting is critical for reliable power system operation, and the search for enhanced methodologies has been a constant field of investigation, particularly in an increasingly competitive environment where the market operator and its p...
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Iouliia Skliarova
This paper proposes a Field-Programmable Gate Array (FPGA)-based hardware accelerator for assisting the embedded MicroBlaze soft-core processor in calculating population count. The population count is frequently required to be executed in cyber-physical ...
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Lukas Tuggener, Mohammadreza Amirian, Fernando Benites, Pius von Däniken, Prakhar Gupta, Frank-Peter Schilling and Thilo Stadelmann
We present an extensive evaluation of a wide variety of promising design patterns for automated deep-learning (AutoDL) methods, organized according to the problem categories of the 2019 AutoDL challenges, which set the task of optimizing both model accur...
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Fernando Merchan, Ariel Guerra, Héctor Poveda, Héctor M. Guzmán and Javier E. Sanchez-Galan
We evaluated the potential of using convolutional neural networks in classifying spectrograms of Antillean manatee (Trichechus manatus manatus) vocalizations. Spectrograms using binary, linear and logarithmic amplitude formats were considered. Two deep c...
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A.S. Kuznetsov,E.Y. Semenov,L.D. Matrosova
Pág. 42 - 47
The article deals with the stages of solving image clustering problems using pre-trained neural networks. Some composite solutions of the clustering problem are presented, where clustering methods are used at the last stage, and most of the work is the e...
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Fedor Krasnov
Pág. 68 - 75
Millions of products are available for online buyers to choose from on Internet marketplaces. Despite all the advantages of diversity, a huge number of possible purchase options can stop and make it difficult to choose, as a result of which buyers leave ...
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