|
|
|
|
|
Myriam Bontonou, Louis Béthune and Vincent Gripon
In the context of few-shot learning, one cannot measure the generalization ability of a trained classifier using validation sets, due to the small number of labeled samples. In this paper, we are interested in finding alternatives to answer the question:...
ver más
|
|
|
|
|
|
|
|
|
|
|
Tala Talaei Khoei and Naima Kaabouch
Intrusion Detection Systems are expected to detect and prevent malicious activities in a network, such as a smart grid. However, they are the main systems targeted by cyber-attacks. A number of approaches have been proposed to classify and detect these a...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hilmil Pradana
Predicting traffic risk incidents in first-person helps to ensure a safety reaction can occur before the incident happens for a wide range of driving scenarios and conditions. One challenge to building advanced driver assistance systems is to create an e...
ver más
|
|
|
|
|
|
|
|
|
|
|
Samuel-Soma M. Ajibade, Festus Victor Bekun, Festus Fatai Adedoyin, Bright Akwasi Gyamfi and Anthonia Oluwatosin Adediran
This study examines the research climate on machine learning applications in renewable energy (MLARE). Therefore, the publication trends (PT) and bibliometric analysis (BA) on MLARE research published and indexed in the Elsevier Scopus database between 2...
ver más
|
|
|
|
|
|
|
|
|
|
|
Akshansh Mishra and Anish Dasgupta
Artificial-intelligence-based algorithms are used in manufacturing to automate difficult activities and discover workflow or process patterns that had never been noticed before. Recent studies deal with the forecasting of the fracture location in dissimi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mohammed Madiafi, Jamal Ezzahar, Kamal Baraka and Abdelaziz Bouroumi
In this paper, we propose a new neural architecture for object classification, made up from a set of competitive layers whose number and size are dynamically learned from training data using a two-step process that combines unsupervised and supervised le...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hugo Silva and Jorge Bernardino
Decision support systems with machine learning can help organizations improve operations and lower costs with more precision and efficiency. This work presents a review of state-of-the-art machine learning algorithms for binary classification and makes a...
ver más
|
|
|
|
|
|
|
|
|
|
|
Saikat Das, Mohammad Ashrafuzzaman, Frederick T. Sheldon and Sajjan Shiva
The distributed denial of service (DDoS) attack is one of the most pernicious threats in cyberspace. Catastrophic failures over the past two decades have resulted in catastrophic and costly disruption of services across all sectors and critical infrastru...
ver más
|
|
|
|
|
|
|
|
|
|
|
Han Hu, Changming Wang, Zhu Liang, Ruiyuan Gao and Bailong Li
Landslides frequently occur because of natural or human factors. Landslides cause huge losses to the economy as well as human beings every year around the globe. Landslide susceptibility prediction (LSP) plays a key role in the prevention of landslides a...
ver más
|
|
|
|
|
|
|
|
|
|
|
Tala Talaei Khoei and Naima Kaabouch
Machine learning techniques have emerged as a transformative force, revolutionizing various application domains, particularly cybersecurity. The development of optimal machine learning applications requires the integration of multiple processes, such as ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Arun Kumar Sangaiah, Samira Rezaei, Amir Javadpour, Farimasadat Miri, Weizhe Zhang and Desheng Wang
Handling faults in a running cellular network can impair the performance and dissatisfy the end users. It is important to design an automatic self-healing procedure to not only detect the active faults, but also to diagnosis them automatically. Although ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sina Keller, Raoul Gabriel and Johanna Guth
Average speed information, which is essential for routing applications, is often missing in the freely available OpenStreetMap (OSM) road network. In this contribution, we propose an estimation framework, including different machine learning (ML) models ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xianglong Wei, Yongjun Lu, Zhili Wang, Xingnian Liu and Siping Mo
Little research has been done on the application of machine learning approaches to evaluating the damage level of river training structures on the Yangtze River. In this paper, two machine learning approaches to evaluating the damage level of spur dikes ...
ver más
|
|
|
|
|
|
|
|
|
|
|
María Consuelo Sáiz-Manzanares, Ismael Ramos Pérez, Adrián Arnaiz Rodríguez, Sandra Rodríguez Arribas, Leandro Almeida and Caroline Françoise Martin
In recent decades, the use of technological resources such as the eye tracking methodology is providing cognitive researchers with important tools to better understand the learning process. However, the interpretation of the metrics requires the use of s...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dawei Luo, Heng Zhou, Joonsoo Bae and Bom Yun
Reliability and robustness are fundamental requisites for the successful integration of deep-learning models into real-world applications. Deployed models must exhibit an awareness of their limitations, necessitating the ability to discern out-of-distrib...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhi Yung Tay, Januwar Hadi, Favian Chow, De Jin Loh and Dimitrios Konovessis
The global greenhouse gas emitted from shipping activities is one of the factors contributing to global warming; thus, there is an urgent need to mitigate the adverse effect of climate change. One of the key strategies is to build a vibrant maritime indu...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ali Salimian, Evan Haine, Cova Pardo-Sanchez, Abul Hasnath and Hari Upadhyaya
The spectral emission data from the plasma glow of various sputtering targets containing indium oxide, zinc oxide, and tin oxide were obtained. The plasma was generated at various power and chamber pressures. These spectral data were then converted into ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jianlei Qiao, Yonglu Lv, Yucai Feng, Chang Liu, Yi Zhang, Jinying Li, Shuang Liu and Xiaohui Weng
At present, the electronic nose has became a new technology for the rapid detection of pesticides. However, the technique may misidentify them for samples that have not been involved in training. Therefore, a hybrid model based on unsupervised and superv...
ver más
|
|
|
|
|
|
|
|
|
|
|
Tran Dinh Khang, Manh-Kien Tran and Michael Fowler
Clustering is an unsupervised machine learning method with many practical applications that has gathered extensive research interest. It is a technique of dividing data elements into clusters such that elements in the same cluster are similar. Clustering...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mayank Kejriwal
Entity Resolution (ER) is the problem of identifying co-referent entity pairs across datasets, including knowledge graphs (KGs). ER is an important prerequisite in many applied KG search and analytics pipelines, with a typical workflow comprising two ste...
ver más
|
|
|
|
|
|