Supervised and Self-Supervised Learning for Assembly Line Action Recognition by Christopher Indris, Fady Ibrahim, Hatem Ibrahem, Götz Bramesfeld, Jie Huo, Hafiz Mughees Ahmad, Syed Khizer Hayat, Guanghui Wang

“…The comparative study was extended to self-supervised learning via a modified SPOT model, which achieved a mAP@IoU=0.1:0.7 of 65% with just 10% of the data labeled using extractor architectures from the fully-supervised portion. Milestones include high scores for both fully and semi-supervised learning on this dataset and improved SPOT performance on ANet1.3. …”
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Perfusion MRI in automatic classification of multiple sclerosis lesion subtypes by Ehsan Homayouny, Rasoul Mahdavifar Khayati, Seyed Massood Nabavi, Vania Karami

“…The overall accuracy of the classification for acute, chronic, and T2 lesion classifications was 96.1%, 90.5%, and 92.9%, respectively. The proposed architectures reached high sensitivity in discrimination between MS lesion subtypes when 3T perfusion MRIs were used.…”
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Active Hard Sample Learning for Violation Action Recognition in Power Grid Operation by Lingwen Meng, Di He, Guobang Ban, Guanghui Xi, Anjun Li, Xinshan Zhu

“…We utilize ResNet50 and ViT architectures with Faster-RCNN for detection and recognition, developed using PyTorch 2.0. …”
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Capter les richesses du patrimoine mondial dans une ville sainte de l’islam : la problématique de la mise en tourisme à Djenné au Mali by Diama Cissouma Togola, Soufian Al Karjousli

“…Depuis, les programmes de développement proposés ont essentiellement visé à préserver le patrimoine architectural de la mosquée et des maisons traditionnelles. …”
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Optimizing Security in IoT Ecosystems Using Hybrid Artificial Intelligence and Blockchain Models: A Scalable and Efficient Approach for Threat Detection by William Villegas-Ch, Jaime Govea, Rommel Gutierrez, Aracely Mera-Navarrete

“…Traditional security solutions, based on centralized architectures, are neither scalable nor efficient enough to handle the increasing complexity and number of IoT devices, leading to high latencies, increased energy consumption, and inadequate intrusion detection. …”
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Advancements in training and deployment strategies for AI-based intrusion detection systems in IoT: a systematic literature review by S. Kumar Reddy Mallidi, Rajeswara Rao Ramisetty

“…It then examines various IDS architectures and delves into the integration of machine learning (ML) and deep learning (DL) technologies that improve detection capabilities and system responsiveness. …”
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Solar photovoltaic panel cells defects classification using deep learning ensemble methods by H. Tella, A. Hussein, S. Rehman, B. Liu, A. Balghonaim, M. Mohandes

“…This study emphasizes the efficacy of integrating various deep learning architectures to augment defect detection precision in photovoltaic systems, enhancing operational reliability and enabling prompt maintenance under challenging environmental conditions.…”
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AI-Assisted Forecasting of a Mitigated Multiple Steam Generator Tube Rupture Scenario in a Typical Nuclear Power Plant by Sonia Spisak, Aya Diab

“…These simulations generated a comprehensive dataset, which served as the foundation for training three ML architectures: Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Convolutional LSTM (CNN+LSTM). …”
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Applying in machine learning and deep learning in finance industry: A case study on repayment prediction by Nguyễn Phát Đạt, Hồ Mai Minh Nhật, Trương Công Vinh, Lê Quang Chấn Phong, Lê Hoành Sử

“…Employed techniques encompass Logistic Regression (LR), K-Nearest Neighbor (KNN), Extreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGBM), in conjunction with deep learning architectures such as Long Short-Term Memory (LSTM) and Artificial Neural Network (ANN). …”
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Real-time event detection using recurrent neural network in social sensors by Van Quan Nguyen, Tien Nguyen Anh, Hyung-Jeong Yang

“…First, a convolutional neural network augmented with multiple word-embedding architectures is used as a text classifier for the pre-processing of the input textual data. …”
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Hybrid Hamiltonian Simulation Approach for the Analysis of Quantum Error Correction Protocol Robustness by Benjamin Gys, Lander Burgelman, Kristiaan De Greve, Georges Gielen, Francky Catthoor

“…The steadily rising numbers of qubits in a single system make the development of small-scale quantum architectures that are able to execute such protocols a pressing challenge. …”
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Communication and Sensing: Wireless PHY-Layer Threats to Security and Privacy for IoT Systems and Possible Countermeasures by Renato Lo Cigno, Francesco Gringoli, Stefania Bartoletti, Marco Cominelli, Lorenzo Ghiro, Samuele Zanini

“…Thirdly, it introduces an architectural proposal, discussing the available choices and tradeoffs to implement such countermeasures, as well as solutions and protocols to preserve the potential benefits of ISAC while ensuring data protection and users’ privacy. …”
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Energy-efficient analog-domain aggregator circuit for RRAM-based neural network accelerators by Khaled Humood, Yihan Pan, Shiwei Wang, Alexander Serb, Themis Prodromakis

“…Recently, there has been notable progress in the advancement of RRAM-based Compute-In-Memory (CIM) architectures, showing promise in accelerating neural networks with remarkable energy efficiency and parallelism. …”
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Revitalizing Art with Technology: A Deep Learning Approach to Virtual Restoration by Nurrohmah Endah Putranti, Shyang-Jye Chang, Muhammad Raffiudin

“…Future research may explore dataset expansion, complex architectures, interdisciplinary collaboration, automated evaluation tools, and improved technologies for real-time restoration applications. …”
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Assessing ECG Interpretation Expertise in Medical Practitioners Through Eye Movement Data and Neuromorphic Models by Syed Mohsin Bokhari, Muhammad Shafi, Fazal Noor, Sarmad Sohaib, Saad Alqahtany, Mark Donnelly

“…Our proposed work combines spiking neuron activations with convolutional and recurrent architectures to analyze spatial and temporal gaze patterns that reflect clinical expertise. …”
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Evaluating Sisal Fiber-Reinforced Gypsum Composites for Water Absorption and Mechanical Performance by Kidane Hadgu Asefa, Temesgen Abrha Tkue, Temesgen Berhanu Yallew

“…The experimental investigation has established sisal fiber as an important reinforcement material for improving the performance of the neat gypsum in a wide range of architectural applications such as ceilings, decorative partitions, and light covers.…”
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Evaluation of Prediction Performances of Deep Learning Models for the Aerodynamic Characteristics of Flettner Rotors by Seo Janghoon, Park Jung Yoon, Ma Juhwan, Kim Young Bu, Park Dong-Woo

“…Three deep learning architectures (U-net, Encoder-Decoder, and Decoder models) are employed and trained to predict the aerodynamic characteristics of Flettner rotors. …”
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Transplanted Endothelial Progenitor Cells Improve Ischemia Muscle Regeneration in Mice by Diffusion Tensor MR Imaging by Xin-Gui Peng, Yingying Bai, Judy R. James, Darya P. Shlapak, Shenghong Ju

“…Diffusion tensor imaging (DTI) was applied to detect the architectural organization of skeletal muscle. This study investigated the feasibility and accuracy of using the DTI to evaluate effectiveness of EPCs treatment. …”
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Exploring In-Network Computing with Information-Centric Networking: Review and Research Opportunities by Marica Amadeo, Giuseppe Ruggeri

“…Traditional cloud computing and edge computing architectures fall short in providing their required flexibility, scalability, and ultra-low latency. …”
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Hybrid Optical Switching for Data Center Networks by Matteo Fiorani, Slavisa Aleksic, Maurizio Casoni

“…Furthermore, the proposed HOS network achieves high transmission efficiency and reduced energy consumption by using two parallel optical switches. We consider the architectures of both a traditional data center network and the proposed HOS network and present a combined analytical and simulation approach for their performance and energy consumption evaluation. …”
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