Gear Classification in Skating Cross-Country Skiing Using Inertial Sensors and Deep Learning by Antonio Pousibet-Garrido, Aurora Polo-Rodríguez, Juan Antonio Moreno-Pérez, Isidoro Ruiz-García, Pablo Escobedo, Nuria López-Ruiz, Noel Marcen-Cinca, Javier Medina-Quero, Miguel Ángel Carvajal

“…The aim of this current work is to identify three different gears of cross-country skiing utilizing embedded inertial measurement units and a suitable deep learning model. …”
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Internet of Things-Based Smart Infant-Incubators Using Machine Learning Analysis by Mahmoud Gamal, Ibrahim Radi, Amr Yousef, and Ali Gaber Mohamed Ali

“…With the different technologies used in this monitoring system, parents have the ability to listen to their babies remotely through a mobile application. …”
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Adversarial liveness detector: Leveraging adversarial perturbations in fingerprint liveness detection by Antonio Galli, Michela Gravina, Stefano Marrone, Domenico Mattiello, Carlo Sansone

“…The procedure can be adapted to different CNNs, adversarial fingerprint algorithms and fingerprint scanners, making the proposed approach versatile and easily customisable todifferent working scenarios. …”
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Multi-Scale Hierarchical Feature Fusion for Infrared Small-Target Detection by Yue Wang, Xinhong Wang, Shi Qiu, Xianghui Chen, Zhaoyan Liu, Chuncheng Zhou, Weiyuan Yao, Hongjia Cheng, Yu Zhang, Feihong Wang, Zhan Shu

“…The inclusion of a boundary difference loss further optimizes the edge details of targets. …”
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DMA‐Net: A dual branch encoder and multi‐scale cross attention fusion network for skin lesion segmentation by Guangyao Zhai, Guanglei Wang, Qinghua Shang, Yan Li, Hongrui Wang

“…Additionally, to enhance the feature interaction and fusion of local and global information, a multi‐scale cross attention fusion module is adopted to cross‐merge features in different directions and at different scales, maximizing the advantages of the dual‐branch encoder and achieving precise segmentation of skin lesions. …”
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Research on RF Intensity Temperature Sensing based on 1D-CNN by DING Meiqi, GUI Lin, WANG Ziyi, SHANG Disen, QIAN Min, LI Qiankun

“…【Objective】In order to improve the accuracy and efficiency of temperature sensing, the application of Microwave Photonic Filter (MPF) based on One-Dimensional Convolutional Neural Network (1D-CNN) in Radio Frequency (RF) intensity temperature sensing is studied.…”
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Prognostic and therapeutic potential of disulfidptosis-related genes in colon adenocarcinoma: a comprehensive multi-omics study by Ye Song, Haoran Zhu, Junyang Wei, Shanxue Yin

“…The ProjecTILs algorithm identified a higher proportion of Th1 cells, while Graph Convolutional Network (GCN) analysis showed no significant differences in T cell subtype proportions across different phenotypes. …”
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Cyber-Physical System Security for Manufacturing Industry 4.0 Using LSTM-CNN Parallel Orchestration by Salman Saeidlou, Nikdokht Ghadiminia, Kwadwo Oti-Sarpong

“…Interoperability among different machines, systems, and humans connected via the Internet of Things (IoT) has blessed Industry 4.0 with numerous advantages over the years. …”
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Spacecraft Intelligent Fault Diagnosis under Variable Working Conditions via Wasserstein Distance-Based Deep Adversarial Transfer Learning by Gang Xiang, Kun Tian

“…However, the problems that data in source and target domains usually have different probability distributions because of different working conditions and there are insufficient labeled or even unlabeled data in target domain significantly deteriorate the performance and generalization of deep fault diagnosis models. …”
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Navigating the Challenges and Opportunities of Tiny Deep Learning and Tiny Machine Learning in Lung Cancer Identification by Yasir Salam Abdulghafoor, Auns Qusai Al-Neami, Ahmed Faeq Hussein

“…More than 70 state-of-the-art articles (from 2019 to 2024) were extensively explored to highlight the different machine learning and deep learning (DL) techniques of different models used for the detection, classification, and prediction of cancerous lung tumors. …”
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Application of artificial intelligence technologies for the detection of early childhood caries by Priyanka A, Rishi Sreekumar, S Namasivaya Naveen

“…This study mainly focuses on the different risk factors, dental caries indexes, and the importance of early caries prediction and treatment. …”
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Are baboons learning "orthographic" representations? Probably not. by Maja Linke, Franziska Bröker, Michael Ramscar, Harald Baayen

“…The ability of Baboons (papio papio) to distinguish between English words and nonwords has been modeled using a deep learning convolutional network model that simulates a ventral pathway in which lexical representations of different granularity develop. …”
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An example of the application of artificial intelligence models in human resources processes by Mustafa Kemal Aydın, Berk Küçük, Selim Sürücü

“…In the second stage, the resumes of the applicants are analyzed using three different deep learning models such as CNN (Convolutional Neural Network), GRU (Gated Recurrent Unit), and LSTM (Long Short-Term Memory) for classification purposes. …”
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Bridging the Gap in Facial Age Progression: An Attention Mechanism Approach by Taoli Liu, Yubin Liang, Wenchen Wu, Yize Tang

“…Our model effectively captures the subtleties of facial aging across different demographics. Extensive experiments and ablation studies demonstrate that our approach excels in preserving identity, ensuring racial consistency, and generating realistic aging effects. …”
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Deep learning‐based dose prediction for low‐energy electron beam superficial radiotherapy by Jialin Huang, Zhitao Dai, Shuai Hu, Yuanchun Ye, Yuling Chen, Ming Li, Tianye Niu, Jinfen Zheng, Yongsheng Huang, Yuanjie Bi

“…Results The C3D model demonstrated significant improvements over traditional 3D U‐Net models, achieving a minimum Gamma pass rate of 92.09% and a minimum dose difference pass rate of 93.58%. The model completed dose predictions in just 0.42 seconds, making predictions approximately 140,000 times faster than MC simulations. …”
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FAHM: Frequency-Aware Hierarchical Mamba for Hyperspectral Image Classification by Peixian Zhuang, Xiaochen Zhang, Hao Wang, Tianxiang Zhang, Leiming Liu, Jiangyun Li

“…However, existing Mamba-based approaches flatten 2-D images into 1-D sequences, inevitably disrupting 2-D local dependencies, thereby disregarding the distinctive difference between high-frequency and low-frequency components in the frequency domain. …”
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Spherical harmonics texture extraction for versatile analysis of biological objects. by Oane Gros, Josiah B Passmore, Noa O Borst, Dominik Kutra, Wilco Nijenhuis, Timothy Fuqua, Lukas C Kapitein, Justin M Crocker, Anna Kreshuk, Simone Köhler

“…The characterization of phenotypes in cells or organisms from microscopy data largely depends on differences in the spatial distribution of image intensity. …”
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Precision diagnosis of tomato diseases for sustainable agriculture through deep learning approach with hybrid data augmentation by Kamaldeep Joshi, Sahil Hooda, Archana Sharma, Humira Sonah, Rupesh Deshmukh, Narendra Tuteja, Sarvajeet Singh Gill, Ritu Gill

“…The study addresses different challenges faced throughout the model development process, like data scarcity and imbalances. …”
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Research on Upper Limb Motion Intention Classification and Rehabilitation Robot Control Based on sEMG by Tao Song, Kunpeng Zhang, Zhe Yan, Yuwen Li, Shuai Guo, Xianhua Li

“…To avoid the drawbacks of modeling methods, traditional machine learning and deep learning methods are employed to perform a nine-class classification task on the sEMG data, comparing the classification accuracy of different approaches. Finally, the motor intentions extracted using a multi-stream convolutional neural network (MLCNN) are utilized to control the iReMo^® end-effector rehabilitation robot, with the system’s motion smoothness and accuracy evaluated through tests involving different trajectories.…”
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An Explainable Model Using Graph-Wavelet for Predicting Biophysical Properties of Proteins and Measuring Mutational Effects by Shreya Mishra, Neetesh Pandey, Atul Rawat, Divyanshu Srivastava, Arjun Ray, Vibhor Kumar

“…Proteins hold multispectral patterns of different kinds of physicochemical features of amino acids in their structures, which can help understand proteins’ behavior. …”
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