Attention-Based Multi-Learning Approach for Speech Emotion Recognition With Dilated Convolution by Samuel, Kakuba, Alwin, Poulose

“…The success of deep learning in speech emotion recognition has led to its application in resource-constrained devices. …”
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Rapid literature mapping on the recent use of machine learning for wildlife imagery by Nakagawa, Shinichi, Lagisz, Malgorzata, Francis, Roxane, Tam, Jessica, Li, Xun, Elphinstone, Andrew, Jordan, Neil R., O'Brien, Justine K., Pitcher, Benjamin J., Van Sluys, Monique, Sowmya, Arcot, Kingsford, Richard T.

“…Machine (especially deep) learning algorithms are changing the way wildlife imagery is processed. …”
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Effect of flipped classroom method on the reflection ability in nursing students in the professional ethics course; Solomon four-group design by Mohammad Rasool Khazaei, Eshagh Moradi, Azizeh Barry, Mohammad Hasan Keshavarzi, Akram Hashemi, Ghobad Ramezani, Atefeh Zabihi Zazoli, Farzaneh Farzadnia

“…Conclusion Considering that there are controversial issues in the course of professional ethics, this method can be effective in the field of deep learning of students.…”
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A pilot study on diabetes detection using handheld fundus camera and mobile app development by Hamada R. H. Al-Absi, Gilbert Njihia Muchori, Saleh Musleh, Syed Abdullah Basit, Mohammad Tariqul Islam, Younss Ait Mou, Tanvir Alam

“…Subsequently, we developed a deep learning model for early diagnosis of diabetes based on fundus image only. …”
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A robust adaptive meta-sample generation method for few-shot time series prediction by Chao Zhang, Defu Jiang, Kanghui Jiang, Jialin Yang, Yan Han, Ling Zhu, Libo Tao

“…Researchers can achieve effective TSP based on the deep learning model and a large amount of data. However, when sufficient high-quality data are not available, the performance of prediction models based on deep learning techniques may degrade. …”
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Automated Detection of Macular Diseases by Optical Coherence Tomography and Artificial Intelligence Machine Learning of Optical Coherence Tomography Images by Soichiro Kuwayama, Yuji Ayatsuka, Daisuke Yanagisono, Takaki Uta, Hideaki Usui, Aki Kato, Noriaki Takase, Yuichiro Ogura, Tsutomu Yasukawa

“…The purpose of this study is to test deep learning with image augmentation for automated detection of chorioretinal diseases. …”
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Intelligent model for forecasting fluctuations in the gold price by Mahdieh Tavassoli, Mahnaz Rabeei, Kiamars Fathi Hafshejani

“…The study also employed Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Multi-Layer Perceptron (MLP) neural network models in deep learning mode to predict gold price fluctuations. …”
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A Review of Agricultural Film Mapping: Current Status, Challenges, and Future Directions by Mengmeng Zhang, Jinwei Dong, Quansheng Ge, Hasituya, Pengyu Hao

“…Deep learning has apparent advantages than traditional machine learning algorithms in extracting PGs details, rarely used for mapping PMF. …”
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A Radiograph Dataset for the Classification, Localization, and Segmentation of Primary Bone Tumors by Shunhan Yao, Yuanxiang Huang, Xiaoyu Wang, Yiwen Zhang, Ian Costa Paixao, Zhikang Wang, Charla Lu Chai, Hongtao Wang, Dinggui Lu, Geoffrey I Webb, Shanshan Li, Yuming Guo, Qingfeng Chen, Jiangning Song

“…With the recent advancement in deep learning algorithms, there is a surge of interest in computer-aided diagnosis of primary bone tumors. …”
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An Effective Dataset Preprocessing Method in Tilted Gear Defects Target Detection by Lifen Tu, Qi Peng, Aiqun Zhang, Xiao Yang, Jiaqi Wang

“…Gear defect detection is a crucial component in power automation systems. Methods based on deep learning have exhibited excellent performance in detecting gears. …”
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Bearing Defect Detection with Unsupervised Neural Networks by Jianqiao Xu, Zhaolu Zuo, Danchao Wu, Bing Li, Xiaoni Li, Deyi Kong

“…Therefore, the defect detection of the bearing has always been the focus of the bearing quality control. Deep learning has been successfully applied to the objection detection due to its excellent performance. …”
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FERA-Net: A Novel Algorithm for Mars Water-Ice Cloud Segmentation Integrating Feature Enhancement, Residual, and Attention Mechanisms by Xu Ma, Jialong Lai, Zhicheng Zhong, Feifei Cui

“…Experimental results demonstrate that, compared to existing deep learning methods, FERA-Net achieves significant improvements in the task of Martian water-ice cloud segmentation. …”
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Development of metastasis and survival prediction model of luminal and non-luminal breast cancer with weakly supervised learning based on pathomics by Hui Liu, Linlin Ying, Xing Song, Xueping Xiang, Shumei Wei

“…In this study, our objective is to develop a deep learning model utilizing pathological images to predict the metastasis and survival outcomes for breast cancer patients. …”
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Evaluating GRU Algorithm and Double Moving Average for Predicting USDT Prices: A Case Study 2017-2024 by RAHMAT, Munirul ula, Zara Yunizar

“…While DMA is well-suited for stable trends and GRU excels in volatile conditions, LSTM outperforms both, reinforcing the effectiveness of deep learning for financial time-series forecasting.…”
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Application and research prospects of artificial intelligence in breast cancer pathological diagnosis by DA Qian, RUAN Miao, FEI Xiaochun, WANG Chaofu

“…With the advent of digital pathology slide scanners and the continuous evolution of deep learning algorithms, there has been a significant advancement in the application of artificial intelligence (AI) in the diagnosis and treatment of breast cancer. …”
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UK Biobank MRI data can power the development of generalizable brain clocks: A study of standard ML/DL methodologies and performance analysis on external databases by Marco Capó, Silvia Vitali, Georgios Athanasiou, Nicole Cusimano, Daniel García, Garth Cruickshank, Bipin Patel

“…In this study, we present a comprehensive pipeline to train and compare a broad spectrum of machine learning and deep learning brain clocks, integrating diverse preprocessing strategies and correction terms. …”
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Pendeteksi Citra Masker Wajah Menggunakan CNN dan Transfer Learning by Mohammad Farid Naufal, Selvia Ferdiana Kusuma

“…Convolutional Neural Network (CNN) merupakan algoritma deep learning yang memiliki performa bagus dalam klasifikasi citra. …”
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Field Development Optimization for Low-Productivity Gas Wells under Intermittent Production by Wei Tian, Yi Liu, Xuri Li, Youliang Jia, Yixuan Wang, Li Li, Zhengyan Zhao, Weihong Ding, Wenxin Zhou, Wenyue Sun

“…Therefore, an optimization method for intermittent gas wells based on particle swarm optimization (PSO) algorithm and deep-learning model is proposed. The PSO algorithm determines the optimal schedule, while the deep-learning model forecasts key cycle parameters for these potential schedules. …”
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Performance of artificial intelligence on cervical vertebral maturation assessment: a systematic review and meta-analysis by Termeh Sarrafan Sadeghi, Seyed AmirHossein Ourang, Fatemeh Sohrabniya, Soroush Sadr, Parnian Shobeiri, Saeed Reza Motamedian

“…Abstract Background Artificial intelligence (AI) methods, including machine learning and deep learning, are increasingly applied in orthodontics for tasks like assessing skeletal maturity. …”
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Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions by Francesco Prendin, Olivia Streicher, Giacomo Cappon, Eva Rolfes, David Herzig, Lia Bally, Andrea Facchinetti

“…In view of this, we developed various algorithms based on linear and deep learning models to forecast PBH episodes in the short-term. …”
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