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Mohammad Mustafa Taye
In recent years, deep learning (DL) has been the most popular computational approach in the field of machine learning (ML), achieving exceptional results on a variety of complex cognitive tasks, matching or even surpassing human performance. Deep learnin...
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Roseline Oluwaseun Ogundokun, Rytis Maskeliunas, Sanjay Misra and Robertas Damasevicius
Posture detection targets toward providing assessments for the monitoring of the health and welfare of humans have been of great interest to researchers from different disciplines. The use of computer vision systems for posture recognition might result i...
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Manuel Lopez-Martin, Antonio Sanchez-Esguevillas, Luis Hernandez-Callejo, Juan Ignacio Arribas and Belen Carro
This work brings together and applies a large representation of the most novel forecasting techniques, with origins and applications in other fields, to the short-term electric load forecasting problem. We present a comparison study between different cla...
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Despoina Mouratidis and Katia Lida Kermanidis
Machine translation is used in many applications in everyday life. Due to the increase of translated documents that need to be organized as useful or not (for building a translation model), the automated categorization of texts (classification), is a pop...
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Despoina Mouratidis and Katia Lida Kermanidis
Machine translation is used in many applications in everyday life. Due to the increase of translated documents that need to be organized as useful or not (for building a translation model), the automated categorization of texts (classification), is a pop...
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Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah and Malak EL-Amir
Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as...
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Normaisharah Mamat, Mohd Fauzi Othman, Rawad Abdoulghafor, Samir Brahim Belhaouari, Normahira Mamat and Shamsul Faisal Mohd Hussein
The implementation of intelligent technology in agriculture is seriously investigated as a way to increase agriculture production while reducing the amount of human labor. In agriculture, recent technology has seen image annotation utilizing deep learnin...
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Jiarui Xia and Yongshou Dai
Ground roll noise suppression is a crucial step in processing deep pre-stack seismic data. Recently, supervised deep learning methods have gained popularity in this field due to their ability to adaptively learn and extract powerful features. However, th...
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Maryam Alzaid and Fethi Fkih
It is crucial to analyze opinions about the significant shift in education systems around the world, because of the widespread use of e-learning, to gain insight into the state of education today. A particular focus should be placed on the feedback from ...
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Adi Wibowo, Joga Dharma Setiawan, Hadha Afrisal, Anak Agung Sagung Manik Mahachandra Jayanti Mertha, Sigit Puji Santosa, Kuncoro Budhi Wisnu, Ambar Mardiyoto, Henri Nurrakhman, Boyi Kartiwa and Wahyu Caesarendra
Human eyes generally perform product defect inspection in Indonesian industrial production lines; resulting in low efficiency and a high margin of error due to eye tiredness. Automated quality assessment systems for mass production can utilize deep learn...
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Fawaz Khaled Alarfaj and Jawad Abbas Khan
The online spread of fake news on various platforms has emerged as a significant concern, posing threats to public opinion, political stability, and the dissemination of reliable information. Researchers have turned to advanced technologies, including ma...
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Farheen Chincholi and Harald Koestler
Hemorrhages in the retinal fundus are a common symptom of both diabetic retinopathy and diabetic macular edema, making their detection crucial for early diagnosis and treatment. For this task, the aim is to evaluate the performance of two pre-trained and...
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Christian Moya and Guang Lin
The Deep Operator Network (DeepONet) framework is a different class of neural network architecture that one trains to learn nonlinear operators, i.e., mappings between infinite-dimensional spaces. Traditionally, DeepONets are trained using a centralized ...
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Beipo Su, Yongfeng Ju and Liang Dai
Video application is a research hotspot in cooperative vehicle-infrastructure systems (CVIS) which is greatly related to traffic safety and the quality of user experience. Dealing with large datasets of feedback from complex environments is a challenge w...
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Wenzel Pilar von Pilchau, Anthony Stein and Jörg Hähner
State-of-the-art Deep Reinforcement Learning Algorithms such as DQN and DDPG use the concept of a replay buffer called Experience Replay. The default usage contains only the experiences that have been gathered over the runtime. We propose a method called...
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Igor Ryazanov, Amanda T. Nylund, Debabrota Basu, Ida-Maja Hassellöv and Alexander Schliep
Driven by the unprecedented availability of data, machine learning has become a pervasive and transformative technology across industry and science. Its importance to marine science has been codified as one goal of the UN Ocean Decade. While increasing a...
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Thien Khai Tran and Tuoi Thi Phan
Sentiment analysis is an active research area in natural language processing. The task aims at identifying, extracting, and classifying sentiments from user texts in post blogs, product reviews, or social networks. In this paper, the ensemble learning mo...
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Shu Lih Oh, Jahmunah Vicnesh, Edward J Ciaccio, Rajamanickam Yuvaraj and U Rajendra Acharya
A computerized detection system for the diagnosis of Schizophrenia (SZ) using a convolutional neural system is described in this study. Schizophrenia is an anomaly in the brain characterized by behavioral symptoms such as hallucinations and disorganized ...
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Lili Fan, Hongwei Zhao, Haoyu Zhao, Pingping Liu and Huangshui Hu
Image retrieval applying deep convolutional features has achieved the most advanced performance in most standard benchmark tests. In image retrieval, deep metric learning (DML) plays a key role and aims to capture semantic similarity information carried ...
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Li-Na Wang, Hongxu Wei, Yuchen Zheng, Junyu Dong and Guoqiang Zhong
Ensemble learning, online learning and deep learning are very effective and versatile in a wide spectrum of problem domains, such as feature extraction, multi-class classification and retrieval. In this paper, combining the ideas of ensemble learning, on...
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