A dataset of blood slide images for AI-based diagnosis of malariaDataverse by Rose Nakasi, Joyce Nakatumba Nabende, Jeremy Francis Tusubira, Aloyzius Lubowa Bamundaga, Alfred Andama

“…The datasets will support robust and accurate deep learning models for malaria diagnosis using thick and thin blood smear images with reasonable detection accuracies.…”
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Custom YOLO Object Detection Model for COVID-19 Diagnosis by Noor Najah Ali, Aseel Hameed, Asanka G. Perera, Ali Al_Naji

“…Clinical staff can benefit from Computer Aided Diagnostics (CAD) systems that combine deep learning algorithms and image processing technologies as diagnostic tools for COVID-19. …”
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Vibration Analysis for Machine Monitoring and Diagnosis: A Systematic Review by Mohamad Hazwan Mohd Ghazali, Wan Rahiman

“…A combination of time domain statistical features and deep learning approaches is expected to be widely applied in the future, where fault features can be automatically extracted from the raw vibration signals. …”
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Rolling bearing fault diagnosis based on parameter optimized VMD and improved GoogLeNet by LI Haoran, LIU Deping

“…ObjectiveThe application of deep learning methods in the field of rolling bearing fault diagnosis is very effective, but traditional neural networks cannot extract features at multiple scales due to the use of a single scale convolution kernel, and do not consider the importance of different features in fault diagnosis. …”
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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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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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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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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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A Deep Graph-Embedded LSTM Neural Network Approach for Airport Delay Prediction by Weili Zeng, Juan Li, Zhibin Quan, Xiaobo Lu

“…On this basis, a diffusion convolution kernel is constructed to capture characteristics of delay propagation between airports, and it is further integrated into the sequence-to-sequence LSTM neural network to establish a deep learning framework for delay prediction. We name this model as deep graph-embedded LSTM (DGLSTM). …”
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Algorithmic emergence? Epistemic in/justice in AI-directed transformations of healthcare by Imo Emah, SJ Bennett

“…Moves toward integration of Artificial Intelligence (AI), particularly deep learning and generative AI-based technologies, into the domains of healthcare and public health have recently intensified, with a growing body of literature tackling the ethico-political implications of this. …”
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The Improvement of Automated Crack Segmentation on Concrete Pavement with Graph Network by Jiang Chen, Ye Yuan, Hong Lang, Shuo Ding, Jian John Lu

“…Recent research on pavement crack detection based on deep learning has laid a good foundation for automated crack segmentation, but there can still be improvements. …”
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Comparison of Fully Convolutional Networks and U-Net for Optic Disc and Optic Cup Segmentation by Jin Zixiao

“…This work presents the contribution of the deep learning models in improving glaucoma screening and therefore helping in avoiding blindness.…”
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Biologically Inspired Spatial–Temporal Perceiving Strategies for Spiking Neural Network by Yu Zheng, Jingfeng Xue, Jing Liu, Yanjun Zhang

“…However, current mainstream DNN (deep learning neural network)-based AI (artificial intelligence) is a ‘black box’. …”
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Evaluating Large Language Models for Optimized Intent Translation and Contradiction Detection Using KNN in IBN by Muhammad Asif, Talha Ahmed Khan, Wang-Cheol Song

“…This research addresses these gaps by evaluating advanced Large Language Models (LLMs) such as BERT-base uncased (BERT-bu), GPT2, LLaMA3, Claude2 and small deep learning model BiLSTM with attention for translating intents and detecting contradictions. …”
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