A comparative analysis of deep learning models for assisting in the diagnosis of periapical lesions in periapical radiographs by Jian Liu, Chaoran Jin, Xiaolan Wang, Kexu Pan, Zhuoyang Li, Xinxuan Yi, Yu Shao, Xiaodong Sun, Xijiao Yu

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Computer vision-based road lane glass beads quality analysis system using ANN by Gi-sang Kang, Jong-Jae Lee, Jong Woo Kim, Seung Wan Seo, Hoki Ban

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Artificial Intelligence in the Oil and Gas Industry: Applications, Challenges, and Future Directions by Marcelo dos Santos Póvoas, Jéssica Freire Moreira, Severino Virgínio Martins Neto, Carlos Antonio da Silva Carvalho, Bruno Santos Cezario, André Luís Azevedo Guedes, Gilson Brito Alves Lima

“…In the second step, the research focused on the OnePetro database, widely used by the oil industry, selecting articles with terms associated with production and drilling, such as “production system”, “hydrate formation”, “machine learning”, “real-time”, and “neural network”. The results highlight the transformative impact of AI on production operations, with key applications including optimizing operations through real-time data analysis, predictive maintenance to anticipate failures, advanced reservoir management through improved modeling, image and video analysis for continuous equipment monitoring, and enhanced safety through immediate risk detection. …”
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Automated Foveal Avascular Zone Segmentation in Optical Coherence Tomography Angiography Across Multiple Eye Diseases Using Knowledge Distillation by Peter Racioppo, Aya Alhasany, Nhuan Vu Pham, Ziyuan Wang, Giulia Corradetti, Gary Mikaelian, Yannis M. Paulus, SriniVas R. Sadda, Zhihong Hu

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Hyperspectral identification of travertine state in Huanglong by the PSO-BPNN method by Menghui Xu, Weihong Wang, Jialun Cai, Qunwei Dai, Jing Fan, Sicheng Li

“…The Siamese network method was employed to generate data labels, and the spectral features of the travertine formations were extracted by combining the sensitive bands with pre-processed and reduced data. …”
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A Hybrid Strategy-Improved SSA-CNN-LSTM Model for Metro Passenger Flow Forecasting by Jing Liu, Qingling He, Zhikun Yue, Yulong Pei

“…Simulation experiments were conducted using card swipe data from Harbin Metro Line 1. The results show that the ISSA provides a more accurate optimization with the average values and standard deviations of the 12 benchmark test function simulations being closer to the optimal values. …”
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FilletCam AI: A handheld tool for precise fillet color profiling of Atlantic salmon and rainbow trout by Rakesh Ranjan, Harsh Shroff, Kata Sharrer, Scott Tsukuda, Christopher Good

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A multi-model approach for estimation of ash yield in coal using Fourier transform infrared spectroscopy by Sameeksha Mishra, Anup K. Prasad, Arya Vinod, Anubhav Shukla, Shailayee Mukherjee, Bitan Purkait, Atul K. Varma, Bhabesh C. Sarkar

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Intelligent rehabilitation in an aging population: empowering human-machine interaction for hand function rehabilitation through 3D deep learning and point cloud by Zhizhong Xing, Zhizhong Xing, Zhizhong Xing, Zhijun Meng, Gengfeng Zheng, Guolan Ma, Lin Yang, Lin Yang, Xiaojun Guo, Li Tan, Yuanqiu Jiang, Huidong Wu

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Structural Similarity-Guided Siamese U-Net Model for Detecting Changes in Snow Water Equivalent by Karim Malik, Colin Robertson

“…In most analyses, high-temporal-resolution SWE and SD data are aggregated into monthly and yearly averages to detect and characterize changes. …”
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Performance degradation assessment method for linear motor feed systems driven by digital twins by Zeqing Yang, Yiding Yao, Wei Cui, Yingshu Chen, Beibei Liu, Yi Jin, Yanrui Zhang, Hongwei Zhao, Guofeng Zhang, Wei Yi, Zonghua Zhang

“…The model first converts one-dimensional time-series data into two-dimensional images using GAF encoding, and then utilizes the image recognition capabilities of AlexNet to assess the degradation state of the linear motor feeding system. …”
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Мethods of Machine Learning in Ophthalmology: Review by D. D. Garri, S. V. Saakyan, I. P. Khoroshilova-Maslova, A. Yu. Tsygankov, O. I. Nikitin, G. Yu. Tarasov

“…By using of machine learning methods, it’s possible to find out, identify and count almost any pathological signs of diseases by analyzing medical images, clinical and laboratory data. Machine learning includes models and algorithms that mimic the architecture of biological neural networks. …”
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SBAS-InSAR Analysis of tectonic derived ground deformation and subsidence susceptibility mapping via machine learning in Quetta City, Pakistan by Sajid Hussain, Bin Pan, Zeeshan Afzal, Meer Muhammad Sajjad, Najeebullah Kakar, Nisar Ahmed, Wajid Hussain, Muhammad Ali

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Enhancing Thyroid Nodule Assessment With UTV-ST Swin Kansformer: A Multimodal Approach to Predict Invasiveness by Yufang Zhao, Yue Li, Yanjing Zhang, Xiaohui Yan, Guolin Yin, Liping Liu

“…By analyzing ultrasound video features using the Video Swin Transformer and clinical data using a text analysis module based on the KAN network, and then fusing these features, the model achieves a classification accuracy of 82.1% and an average AUC of 94.2%. …”
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Predictors of fairness assessment for social media screening in employee selection by Alicja Balcerak, Jacek Woźniak, Alexandra Zbuchea

“…The results of linear regression with backward elimination indicated that among the assumed factors influencing the perceived justice of Facebook and LinkedIn screening in the selection process (i.e., privacy invasiveness, personal innovativeness, self-image management, risk aversion, ability to control a social networking site’s information, above average performance self-assessment, a general concern for internet privacy, and – in the case of LinkedIn – having an account on LinkedIn) the perceived privacy invasiveness is the best predictor of perceived justice of both private (Facebook), and professional (LinkedIn) social networking site screening for personnel selection purposes. …”
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Fault diagnosis and inference of hoist main bearing based on transfer learning and ontology by Fei DONG, Di ZHANG, Kunpeng GE, Junjie CHEN, Xinyue XU

“…To overcome the challenges still faced by data-driven hoist main bearing fault diagnosis methods, including data imbalance due to a lack of fault samples under real operating conditions, diagnostic performance degradation of fault diagnosis models caused by significant differences in data sample distribution under varying conditions, single fault diagnosis function, and a lack of reasoning analysis and localization for the causes of hoist main bearing system failures, a new fault diagnosis and reasoning method for hoist main bearing systems is studied, which includes two aspects: ① Bearing fault diagnosis based on convolutional neural network transfer learning and domain adaptation. …”
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Segmentation Techniques Applied to CNNs for Cervical Cancer Classification by Ana Ortiz-Gonzalez, Raquel Martinez-Espana, Juan Morales-Garcia, Baldomero Imbernon, Jose Martinez-Mas, Mauricio A. Alvarez, Oscar David Romero, Juan Pedro Martinez-Cendan, Andres Bueno-Crespo

“…In this paper, we design an automatic segmentation masks for the classification of cervicovaginal cell images. This automatic segmentation is combined in a classification model that allows the models to improve their performance thanks to the morphological information provided by the combined segmentation in a Global Average Pooling layer with the convolutional network analysis of the original image. …”
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MRI Screening of Lungs in the COVID-19 Pandemic at the Stages of Medical Care as a Tool to Reduce the Total Collective Dose of Radiation to the Population by A. V. Korobov, N. V. Nudnov, A. Yu. Popov, T. V. Kul’neva, V. V. Babenko, E. V. Pron’kina

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Sustainable AI for plant disease classification using ResNet18 in few-shot learning by Fareeha Naveed, Adven Masih, Jabar Mahmood, Moeez Ahmed, Aitizaz Ali, Aysha Saddiqa, Mohamed Shabbir Hamza Abdulnabi, Ebenezer Agbozo

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Machine learning to identify suitable boundaries for band-pass spectral analysis of dynamic [ $$^{11}$$ 11 C]Ro15-4513 PET scan and voxel-wise parametric map generation by Zeyu Chang, Colm J. McGinnity, Rainer Hinz, Manlin Wang, Joel Dunn, Ruoyang Liu, Mubaraq Yakubu, Paul Marsden, Alexander Hammers

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