Similarity-Based Summarization of Music Files for Support Vector Machines by Jan Jakubik, Halina Kwaśnicka

“…Deep neural network architectures can learn to build feature representations that summarize music files from data itself, rather than expert knowledge. …”
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Non-convex optimization with using positive-negative moment estimation and its application for skin cancer recognition with a neural network by P.A. Lyakhov, U.A. Lyakhova, R.I. Abdulkadirov

“…The introduction of the developed algorithms into the learning process of various architectures of multimodal neural network systems for analyzing heterogeneous data has made it possible to increase the accuracy of recognizing pigmented skin lesions by 2.33 – 5.69 percentage points, compared to the original optimization methods. …”
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Dorothy C. Miller, Chase Manhattan and American Banking: Investing Art? by Christine Zumello

“…And its composition denotes the paramount importance of such new defining artistic, architectural and business trends at the end of the 1950s as corporate modernism, abstraction and new conceptual approaches of business and bank management, as well as the physical space of bank offices and the space devoted to art in almost each single one of those offices. …”
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CS-FL: Cross-Zone Secure Federated Learning with Blockchain and a Credibility Mechanism by Chongzhen Zhang, Hongye Sun, Zhaoyu Shen, Dongyu Wang

“…However, traditional FL architectures face challenges such as centralization and lack of effective defense mechanisms against malicious nodes, particularly in large-scale edge computing scenarios, which can lead to system instability. …”
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Energy-Optimized Monitoring System for Underground Cave Environments Based on Long Preamble LoRa by Mattia Ragnoli, Gianluca Barile, Alfiero Leoni, Stefano Ricci, Vincenzo Stornelli

“…This paper reports the implementation of the whole system, starting from the architectural details to the experimental results obtained in the field.…”
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Deep Learning in Oral Hygiene: Automated Dental Plaque Detection via YOLO Frameworks and Quantification Using the O’Leary Index by Alfonso Ramírez-Pedraza, Sebastián Salazar-Colores, Crystel Cardenas-Valle, Juan Terven, José-Joel González-Barbosa, Francisco-Javier Ornelas-Rodriguez, Juan-Bautista Hurtado-Ramos, Raymundo Ramirez-Pedraza, Diana-Margarita Córdova-Esparza, Julio-Alejandro Romero-González

“…This study focuses on detecting three plaque stages—new, mature, and over-mature—using state-of-the-art YOLO architectures to enhance early intervention and reduce reliance on manual visual assessments. …”
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Research on algorithm for improving imaging accuracy of CFRP low speed impact damage by WU Xiangnan, CHENG Xiaojin, LI Qixin, SHANG Jianhua

“…To address the issue of low imaging precision in C-scan detection of internal damage caused by low-velocity impact in CFRP，gradient operators were employed to process the original images，and transfer learning methodology was utilized to conduct damage classification training on ResNet18 and ResNet50 architectures. To enhance the classification model’s performance，an image reconstruction model（IRM）based on convolutional neural networks was proposed to improve imaging precision. …”
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Scaffolds fabricated via two-photon polymerisation for regulating cell morphology and differentiation by Zheyu Yao, Xiuzhen Zhang, Wenhui Yu, Zhen Xiao, Wenli Zhou, Dongfeng Qi, Wuhong Xin, Weilong Cao, Hongyu Zheng

“…In this study, two-photon polymerisation (TPP) technology was employed to create 3D scaffolds with woodpile and honeycomb architectures. The influence of scaffold geometry and pore dimensions on the proliferation, morphology, orientation, and differentiation of human mesenchymal stem cells (hMSCs) was investigated through multi-staining fluorescence and 3D confocal imaging technique. …”
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Enhanced CATBraTS for Brain Tumour Semantic Segmentation by Rim El Badaoui, Ester Bonmati Coll, Alexandra Psarrou, Hykoush A. Asaturyan, Barbara Villarini

“…Automatic brain tumour segmentation tools in computer vision have integrated powerful deep learning architectures to enable accurate tumour boundary delineation. …”
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A hybrid multiscale feature fusion model for enhanced cardiovascular arrhythmia detection by Md. Alamin Talukder

“…Specifically, we explore two fusion approaches, Hybrid Feature Fusion (HFF) and HMFF, leveraging ConvNeXtTiny, ConvNeXtSmall, and ConvNeXtBase architectures. To mitigate class imbalance, we integrate SMOTE-Tomek Link (STL) and Random Oversampling (RO) strategies, ensuring robust representation of minority classes. …”
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Task-Oriented Adversarial Attacks for Aspect-Based Sentiment Analysis Models by Monserrat Vázquez-Hernández, Ignacio Algredo-Badillo, Luis Villaseñor-Pineda, Mariana Lobato-Báez, Juan Carlos Lopez-Pimentel, Luis Alberto Morales-Rosales

“…To conduct this evaluation, we propose diverse adversarial attacks across different dataset domains, target architectures, and consider distinct levels of victim model knowledge, thus obtaining a comprehensive evaluation. …”
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Comparing Cross-Subject Performance on Human Activities Recognition Using Learning Models by Zhe Yang, Mengjie Qu, Yun Pan, Ruohong Huan

“…In this paper, we evaluate three traditional machine learning methods and five deep neural network architectures under the same metrics on three popular HAR datasets: mHealth, PAMAP2, and UCIDSADS. …”
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DGFEG: Dynamic Gate Fusion and Edge Graph Perception Network for Remote Sensing Change Detection by Shengning Zhou, Genji Yuan, Zhen Hua, Jinjiang Li

“…Numerous networks combining CNN and transformer architectures have emerged, yet effectively balancing local detail and global context features remains a topic of ongoing discussion. …”
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Role of Artificial Intelligence in Oral Cancer by Vidhya Rekha Umapathy, Prabhu Manickam Natarajan, Bhuminathan Swamikannu, Sabarinathan Jaganathan, Suba Rajinikanth, Vijayalakshmi Periyasamy

“…Machine learning paradigms, encompassing supervised and unsupervised learning, afford meticulous classification and pattern identification from multifarious clinical and histopathological datasets. Deep learning architectures, exemplified by convolutional neural networks (CNNs), automatize lesion detection, and characterization from medical imagery, thereby expediting diagnostic efficacy. …”
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Evaluation of Human β-defensin-3 Diagnostic Role in a Group of Iraqi Patients with Osteoporosis by Zahraa S. Hassan, Layla O. Farhan

“… Background: Osteoporosis (OP) is a prevalent age-related condition that increases the risk of fracture and bone fragility, as result loss of bone mass as well as micro-architectural degradation of the bone, thereby reducing the mass and strength of bone. …”
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An Artificial-Intelligence- and Telemedicine-Based Screening Tool to Identify Glaucoma Suspects from Color Fundus Imaging by Alauddin Bhuiyan, Arun Govindaiah, R. Theodore Smith

“…Then, using CDR below 0.5 (nonsuspect) and CDR above 0.5 (glaucoma suspect), deep-learning architectures were used to train and test a binary classifier system. …”
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Forecasting the Probability of Large Rates of Change of the Geomagnetic Field in the UK: Timescales, Horizons, and Thresholds by A. W. Smith, C. Forsyth, I. J. Rae, T. M. Garton, T. Bloch, C. M. Jackman, M. Bakrania

“…We assess the ability of three different machine learning model architectures to process the time history of the incoming solar wind and provide a probabilistic forecast as to whether the rate of change of the ground magnetic field will exceed specific high thresholds at a location in the UK. …”
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A Modified Implementation of Tristate Inverter Based Static Master-Slave Flip-Flop with Improved Power-Delay-Area Product by Kunwar Singh, Satish Chandra Tiwari, Maneesha Gupta

“…The paper introduces novel architectures for implementation of fully static master-slave flip-flops for low power, high performance, and high density. …”
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MoE-NuSeg: Enhancing nuclei segmentation in histology images with a two-stage Mixture of Experts network by Xuening Wu, Yiqing Shen, Qing Zhao, Yanlan Kang, Wenqiang Zhang

“…While state-of-the-art Transformer-based models employ tri-decoder architectures to decouple the segmentation task into nuclei, edges, and cluster edges segmentation, their complexity and long inference times hinder clinical integration. …”
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Transfer Learning-Based Health Monitoring of Robotic Rotate Vector Reducer Under Variable Working Conditions by Muhammad Umar Elahi, Izaz Raouf, Salman Khalid, Faraz Ahmad, Heung Soo Kim

“…Fine-tuning pre-trained architectures on operational data for the three different reducers of health conditions, which are healthy, faulty, and faulty aged, improves fault classification across different motion profiles and variable speed conditions. …”
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