3D landmark‐based face restoration for recognition using variational autoencoder and triplet loss by Sahil Sharma, Vijay Kumar

“…By using the restored 3D face, a deep learning‐based face recognition system is developed. …”
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A Lightweight Laser Chip Defect Detection Algorithm Based on Improved YOLOv7-Tiny by HU Wei, ZHAO Jumin, LI Dengao

“…In this study, a lightweight laser chip defect detection algorithm based on an improved YOLOv7-Tiny is proposed, aiming at addressing the high computational and parameter demands of deep learning applications in defect detection. [Methods] By employing a lightweight convolutional neural network as the feature extraction backbone and integrating multi-branch reparameterized convolution blocks, this algorithm not only significantly reduces resource consumption but also enhances feature representation capabilities. …”
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A guide for active learning in synergistic drug discovery by Shuhui Wang, Alexandre Allauzen, Philippe Nghe, Vaitea Opuu

“…While AI, particularly deep learning, has advanced synergy predictions, its effectiveness is limited by the low occurrence of synergistic drug pairs. …”
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Antenna Optimization Based on Auto-Context Broad Learning System by Wei-Tong Ding, Fei Meng, Yu-Bo Tian, Hui-Ning Yuan

“…Broad learning system (BLS), as an emerging network with strong extraction ability and remarkable computational efficiency, has revolutionized the conventional artificial intelligence (AI) methods and overcome the shortcoming of excessive time-consuming training process in deep learning (DL). However, it is difficult to model the regression relationship between input and output variables in the electromagnetic field with the unsatisfactory fitting capability of the original BLS. …”
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A Novel Multi-Level Perceptron for Accurate Heart Stroke Diagnosis by Muhammad Zaman, Muhammad Khubaib, Tanzila Kahkashan, Anam Zahoor, Narges Shahbaz, Shahzad Shoukat, Fahma Nisar

“…Different types of Machine Learning and deep learning algorithms are used for heart stroke predictions. …”
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Improved Set-point Tracking Control of an Unmanned Aerodynamic MIMO System Using Hybrid Neural Networks by Oduetse Matsebe, David Mohammed Ezekiel, Ravi Samikannu

“…The training features use the Matlab Deep Learning Toolbox. The NARX structure has its core in the neural networks’ architecture. …”
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Approaches and Conceptions of Teaching and Learning: Towards the School of Excellence by Abílio A. Lourenço, Sabina Valente, Sergio Dominguez-Lara, Celso Fulano

“…The importance of understanding students’ conceptions of their learning situations and acting to enhance teaching contexts where they experience deep learning approaches has also been emphasized, necessarily implying a student-centered approach. …”
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Trivariate Stochastic Weather Model for Predicting Maize Yield by Patrick Chidzalo, Phillip O. Ngare, Joseph K. Mung’atu

“…The trivariate stochastic process predicts maize yield with R2=0.8389 and MAPE=4.31% under a deep learning framework. Its aggregated values predict maize yield with R2 up to 0.9765 and MAPE=1.94% under common machine learning algorithms. …”
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Human‐Induced Climate Change Intensifies Extreme Precipitation Events in Central China's Urban Areas by Yufan Chen, Shuyu Zhang, Hong Wang, Deliang Chen, Junguo Liu

“…Using advanced techniques such as deep learning and optimal fingerprinting, this study identifies and analyzes the physical mechanisms behind the extreme precipitation. …”
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Multimodal deep ensemble classification system with wearable vibration sensor for detecting throat-related events by Yonghun Song, Inyeol Yun, Sandra Giovanoli, Chris Awai Easthope, Yoonyoung Chung

“…Out of the continuous data stream, we automatically classify events of interest using an ensemble-based deep learning model. The proposed model integrates multiple deep neural networks based on multi-modal acoustic features of throat-related events to enhance robustness and accuracy of classification. …”
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Efficient Intrusion Detection System Data Preprocessing Using Deep Sparse Autoencoder with Differential Evolution by Saranya N., Anandakumar Haldorai

“…Many researchers are focused to IDS with machine and deep learning approaches to detect the intruders. Yet, IDS face challenges to detect the intruders accurately with reduced false alarm rate, feature selection, and detection. …”
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Probabilistic Automated Model Compression via Representation Mutual Information Optimization by Wenjie Nie, Shengchuan Zhang, Xiawu Zheng

“…This optimization process is highly practical, requiring merely a few GPU hours, and bridges the gap between theoretical information measures and practical model compression, offering significant insights for efficient deep learning deployment.…”
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Power Prediction-Based Model Predictive Control for Energy Management in Land and Air Vehicle with Turboshaft Engine by Zhengchao Wei, Yue Ma, Changle Xiang, Dabo Liu

“…An integrated power predictor consisting of the classification of input status and the subpredictors are developed based on the deep learning method to improve the accuracy of the prediction model of the model predictive control (MPC). …”
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Application of Enhanced EWT and Enhanced Dictionary Learning in Bearing Faults Identification by Wu Caixia, Li Fan, Liu Yubo

“…When realizing rolling bearing fault identification through deep learning, there is a low recognition rate and convergence rate due to ambient noise. …”
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Deep Neural Networks With Convolutional and LSTM Layers for SYM‐H and ASY‐H Forecasting by Armando Collado‐Villaverde, Pablo Muñoz, Consuelo Cid

“…Their resolution, along with their relation to the solar wind parameters, makes the forecasting of the geomagnetic indices a problem that can be addressed through the use of Deep Learning, particularly using Deep Neural Networks (DNNs). …”
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Video-Based Plastic Bag Grabbing Action Recognition: A New Video Dataset and a Comparative Study of Baseline Models by Pei Jing Low, Bo Yan Ng, Nur Insyirah Mahzan, Jing Tian, Cheung-Chi Leung

“…The third approach explores a 3D CNN-based deep learning model, which is capable of processing video data as volumetric inputs. …”
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Comparative Analysis of Federated and Centralized Learning Systems in Predicting Cellular Downlink Throughput Using CNN by Kukuh Nugroho, Hendrawan, Iskandar

“…The efficacy of the model is compared with Centralized Learning (CL) and other deep learning models, including MLP, RNN, LSTM, and GRU. …”
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Enhancing bowel sound recognition with self-attention and self-supervised pre-training. by Yansuo Yu, Mingwu Zhang, Zhennian Xie, Qiang Liu

“…This study introduces an innovative deep learning-based method designed to automate and enhance the recognition of bowel sounds. …”
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LEHP-DETR: A model with backbone improved and hybrid encoding innovated for flax capsule detection by Changshun Wang, Junying Han, Chengzhong Liu, Jianping Zhang, Yanni Qi

“…The development of computer vision and deep learning techniques offers a new way to solve this problem. …”
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Research on industrial Internet security detection and response based on digital twin by MA Jiali, GUO Yuanbo, FANG Chen, CHEN Qingli, ZHANG Qi

“…Comparing the proposed method with the intrusion detection system based on deep learning, the experimental results show that the detection rate of the proposed method increases by 25%~40.9% in detecting anomalies.…”
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