Lightweight patch-level attention for efficient pig behavior detection: A novel dataset and approach by Shuo Wan, Zhongqiang Huang, Tao Han, Ying Sha

“…Currently, mainstream approaches for pig behavior detection utilize neural networks for image analysis and recognition, however, deep neural network architectures are inherently complex and computationally intensive, with potential for further accuracy enhancement. …”
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La description d’image chez les adultes neurotypiques bilingues : analyse de la performance selon la langue utilisée. by Émilie Godin, Sophie Laurence, Anna Zumbansen, Chantal Mayer-Crittenden

“…La performance à la tâche de description d’image peut varier selon l’âge ou le niveau d’éducation. …”
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ANALYSIS OF INTEGRATION AND DISINTEGRATION IN THE DIGITAL AGE by CORINA GRIBINCEA, SUSAN KHALDOUN KESSEI

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RESEARCH AND EXPERIMENTAL APPROBATION OF PEDAGOGICAL TERMS FOR THE FORMATION OF STUDENTS’ LEADERSHIP SKILLS IN THE INNOVATIVE EDUCATIONAL ENVIRONMENT OF THE LYCEUM by Iermak Tetiana

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Distinct early development trajectories in Nf1 ± and Tsc2 ± mouse models of autism by Helena Ferreira, Sofia Santos, João Martins, Miguel Castelo-Branco, Joana Gonçalves

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Fatal Mycobacterium avium meningitis in an HIV-negative Vietnamese man: a case report by Van Thanh Nguyen, Le Hong Van, Guy Thwaites, Nguyen Thuy Thuong Thuong, Pham Kieu Nguyet Oanh, Do Dang Anh Thu, Nguyen Thanh Dung, Van Thi Xuan Quynh, Nguyen Tran Thuong Dinh, Ho Dang Trung Nghia

“…We describe a case of Mycobacterium avium complex meningitis with cerebral hemorrhage in an human immunodeficiency virus uninfected man in Vietnam. …”
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Deep Learning Approaches for Morphological Classification of Intestinal Organoids by Giovanni Cicceri, Sebastiano Di Bella, Simone Di Franco, Giorgio Stassi, Matilde Todaro, Salvatore Vitabile

“…To date, the classification of organoids is performed manually by microscope and, therefore, in a data-driven application, is time-consuming, inaccurate, and difficult to morphological analysis process. The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. …”
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Can deep learning technology really recognize Mpox? A positive response from the EfficientNet model by Xiaoqian Zhao, Xiaoqian Zhao, Long Lyu, Li Zhang, Li Zhang

“…The model uses EfficientNet as the backbone network and employs transfer learning techniques to transfer the pre-trained EfficientNet parameters, originally trained on the ImageNet dataset, into this model. This approach allows the model to have strong generalization capabilities while controlling the number of parameters and computational complexity. …”
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Enhancing Heart Disease Diagnosis Using ECG Signal Reconstruction and Deep Transfer Learning Classification with Optional SVM Integration by Mostafa Ahmad, Ali Ahmed, Hasan Hashim, Mohammed Farsi, Nader Mahmoud

“…<b>Background/Objectives:</b> Accurate and efficient diagnosis of heart disease through electrocardiogram (ECG) analysis remains a critical challenge in clinical practice due to noise interference, morphological variability, and the complexity of overlapping cardiac signals. …”
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Aesthetic preferences for male breast: Analysis of 2282 surveys on the Chinese population by Saisai Cao, Boyang Wang, Xiangyu Liu

“…Participants were asked to evaluate the images and identify the most attractive male breast. …”
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Detection of hidden defects of thermal protection of buildings and determination of some thermal properties of structural building materials by Non-destructive Thermal Imaging meth... by D. F. Karpov, M. V. Pavlov, A. G. Gudkov

“…The purpose of the work is the practical approbation of a nondestructive thermal imaging method to identify hidden (invisible) defects and qualitative analysis of the thermal protection of a complex of construction objects in the city of Vologda, as well as the study of some physical (thermophysical) indicators (coefficients of thermal conductivity, thermal resistance (thermal insulation) and heat transfer) of structural building material in the form of silicate brick.Method. …”
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Variable Properties of Auditory Scene Analysis in Music by Adam Rosiński

“…This article explores the variable properties of auditory image analysis during the perception of musical works, which are influenced by the specific elements to which the listener directs their attention. …”
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Spatial (mis)match between EEG and fMRI signal patterns revealed by spatio-spectral source-space EEG decomposition by Stanislav Jiricek, Stanislav Jiricek, Stanislav Jiricek, Vlastimil Koudelka, Dante Mantini, Radek Marecek, Jaroslav Hlinka, Jaroslav Hlinka

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Research on an Intelligent Sedimentary Microfacies Recognition Method Based on Convolutional Neural Networks Within the Sequence Stratigraphy of Well Logging Curve Image Groups by Xinyi Yuan, Xidong Wang, Shutian Wang, Feng Tian, Zichun Yang

“…Results demonstrate the model’s capability to identify six microfacies types (e.g., subaqueous distributary channels, estuary bars, sheet sands) with 83% accuracy, significantly surpassing conventional log facies analysis. This breakthrough in interpreting complex heterogeneous reservoir lithofacies establishes a novel technical avenue for intelligent exploration of subtle hydrocarbon reservoirs.…”
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NAF-MEEF: A Nonlinear Activation-Free Network Based on Multi-Scale Edge Enhancement and Fusion for Railway Freight Car Image Denoising by Jiawei Chen, Jianhai Yue, Hang Zhou, Zhunqing Hu

“…Furthermore, the structural complexity of freight cars, coupled with the small size, diversity, and complex structure of defect areas, poses serious challenges for image denoising. …”
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Manually classified dataset of leaning and standing personnel images for construction site monitoring and neural network training(Repositorio Institucional – Universidad de Lima) by Alexandre Almeida Del Savio, Ana Luna Torres, Daniel Cárdenas-Salas, Mónica Vergara Olivera, Gianella Urday Ibarra

“…This dataset addresses the challenges of finding personnel in different poses within complex construction environments. The resource will enhance construction site safety monitoring and personnel activity analysis by allowing more precise neural network training. …”
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BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices by Emre Şafak, İbrahim Alper Doğru, Necaattin Barışçı, İsmail Atacak

“…By converting Android DEX files into image data, BlockDroid leverages the superior image analysis capabilities of CNN models to discern patterns indicative of malware. …”
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Relationship between the degree of myocardial damage according to contrast-enhanced cardiac magnetic resonance imaging and laboratory data in patients with acute myocardial infarct... by O. V. Mochula, A. S. Sulejmanova, A. E. Sukhareva, V. V. Ryabov, K. V. Zavadovsky

“…To evaluate the information value of a complex of clinical and biochemical parameters of myocardial damage in predicting the development of transmural myocardial damage according to magnetic resonance imaging (MRI) in patients with acute myocardial infarction (AMI).Material and methods. …”
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Brain Tumor Detection and Prediction in MRI Images Utilizing a Fine-Tuned Transfer Learning Model Integrated Within Deep Learning Frameworks by Deependra Rastogi, Prashant Johri, Massimo Donelli, Lalit Kumar, Shantanu Bindewari, Abhinav Raghav, Sunil Kumar Khatri

“…Brain tumor diagnosis is a complex task due to the intricate anatomy of the brain and the heterogeneity of tumors. …”
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Deep Learning-Based Brain Tumor Segmentation in MRI Images: A MobileNetV2-DeepLabV3+ Approach by Farhad Abedinzadeh Torghabeh, Seyyed Abed Hosseini

“…Introduction: Brain tumors (BTs) pose significant challenges in medical diagnosis and treatment due to their heterogeneity and complex characteristics. Accurate and precise segmentation of BTs in magnetic resonance images (MRIs) is crucial for effective treatment planning and patient care. …”
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