Explainable Feature-Injected Diffusion Model for Medical Image Translation by Jung Su Ahn, Ki Hoon Kwak, Young-Rae Cho

“…Experimental results demonstrate that EIDM outperforms latest Generative Adversarial Networks (GANs) and diffusion models, generating realistic MR images that preserve anatomical integrity, as evidenced by enhanced scores across evaluation metrics. …”
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Influences on policy-formulation, decision-making, organisation and management for maternal, newborn and child health in Bangladesh, Ethiopia, Malawi and Uganda: The roles and legi... by Kohenour Akter, Yusra Ribhi Shawar, Anene Tesfa, Callie Daniels Howell, Gloria Seruwagi, Agnes Kyamulabi, Albert Dube, Geremew Gonfa, Kasonde Mwaba, QCN Evaluation Group, Mary Kinney, Mike English, Jeremy Shiffman, Nehla Djellouli, Tim Colbourn

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Complementarity-Oriented Feature Fusion for Face-Phone Trajectory Matching by Changfeng Cao, Wenchuan Zhang, Hua Yang, Dan Ruan

“…Specifically, a Cycle Heterogeneous Trajectory Translation Network (CCTTN) is proposed to realize a TFE (Trajectory Feature Extractor) which captures the latent transforming relationships between the face and phone modalities. …”
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Multi-Feature Facial Complexion Classification Algorithms Based on CNN by Xiyuan Cao, Delong Zhang, Chunyang Jin, Zhidong Zhang, Chenyang Xue

“…Precisely categorizing facial complexions poses a significant challenge due to the subtle distinctions in facial features. Three multi-feature facial complexion classification algorithms leveraging convolutional neural networks (CNNs) are proposed. …”
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Data Fusion of Electronic Nose and Multispectral Imaging for Meat Spoilage Detection Using Machine Learning Techniques by Vassilis S. Kodogiannis, Abeer Alshejari

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Circle of Willis variations and features in an American Midwestern cadaver population by Swathi Sridhar, Farida Mehrhoff, Dominic Maiuro, Chloe Maye, Cameron Smith, Phil Sheridan, Robert Hillard

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AI-driven diagnosis and health management of autonomous electric vehicle powertrains: An empirical data-driven approach by Hicham El hadraoui, Adila El maghraoui, Oussama Laayati, Erroumayssae Sabani, Mourad Zegrari, Ahmed Chebak

“…Among the models, the optimized neural network combined with CA-selected features achieved the most consistent diagnostic performance, supported by low root mean square error and balanced evaluation metrics. …”
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A network traffic classification method based on random forest and improved convolutional neural network by Bensheng YUN, Xiaoya GAN, Yaguan QIAN

“…In order to improve the efficiency and reduce the complexity of network traffic classification model, a classification method based on random forest and improved convolutional neural network was proposed.Firstly, the random forest was used to evaluate the importance of each feature of network traffic, and the feature was selected according to the importance ranking.Secondly, AdamW optimizer and triangular cyclic learning rate were adopted to optimize the convolutional neural network classification model.Then, the model was built on Spark cluster to realize the parallelization of model training.Adopting triangular cyclic learning rate with constant cycle amplitude, the experimental results of selecting 1 024, 400, 256 and 100 most important features as input show that the model accuracy is improved to 97.68%, 95.84%, 95.03% and 94.22%, respectively.The 256 most important features were selected and the experimental results based on adopting different learning rates show that the learning rate with half the cycle amplitude works best, the accuracy of the model is improved to 95.25%, and training time of the model is reduced by nearly half.…”
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Visible feature engineering to detect fraud in black and red peppers by Mohammad Hossein Nargesi, Kamran Kheiralipour

“…The efficient features were classified using artificial neural networks and support vector machine methods. …”
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Kronecker convolutional feature pyramid for fault diagnosis in rolling bearings by Sadia Batool, Abbas Ali Abid, Muhammad Asif, Sagheer Abbas, Khan Muhammad Adnan, Asghar Ali Shah, Taher M. Ghazal

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Decom-UNet3+: A Retinal Vessel Segmentation Method Optimized With Decomposed Convolutions by Qun Li, Juntao Zhang, Licheng Hua, Songyin Fu, Chenjie Gu

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YOLO-LSD: A Lightweight Object Detection Model for Small Targets at Long Distances to Secure Pedestrian Safety by Ming-An Chung, Sung-Yun Chai, Ming-Chun Hsieh, Chia-Wei Lin, Kai-Xiang Chen, Shang-Jui Huang, Jun-Hao Zhang

“…The proposed model integrates the C3C2 and the new Efficient Layer Aggregation Network - Convolutional Block Attention Module(ELAN-CBAM) modules to improve the efficiency of feature extraction while reducing computational overhead. …”
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Enhanced Multigrained Scanning-Based Deep Stacking Network for Intrusion Detection in IoMT Networks by Pakarat Musikawan, Yanika Kongsorot, Phet Aimtongkham, Chakchai So-In

“…Drawing inspiration from the accomplishments of deep learning in cyber threat detection, we propose a multigrained scanning-based deep stacking network (MGDSN) to defend against sophisticated cyberattacks on Internet of Medical Things (IoMT) networks. …”
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Intrusion Detection in IoT Networks Using Dynamic Graph Modeling and Graph-Based Neural Networks by William Villegas-Ch, Jaime Govea, Alexandra Maldonado Navarro, Pablo Palacios Jativa

“…The proposed method was evaluated using a customized dataset from a simulated IoT network to reflect real-world attack scenarios, including Denial of Service, Spoofing, and Man-in-the-Middle. …”
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Stability indicators in network reconstruction. by Michele Filosi, Roberto Visintainer, Samantha Riccadonna, Giuseppe Jurman, Cesare Furlanello

“…However, evaluating their performance is unfeasible unless a 'gold standard' is available to measure how close the reconstructed network is to the ground truth. …”
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WirelessNet: An Efficient Radio Access Network Model Based on Heterogeneous Graph Neural Networks by Jose Perdomo, M. A. Gutierrez-Estevez, Chan Zhou, Jose F. Monserrat

“…Model parameters associated to the same underlying wireless phenomena are shared across network nodes. Results using system-level simulations to train and evaluate our proposal, show that WirelessNet efficiently outputs accurate downlink rates and vector representations of users, even for network deployments unseen during training, with significantly less computational runtime than a cellular network simulator and more accuracy than typical neural network architectures. …”
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LANet for medical image segmentation by Di Zhao, Yi Tang, D. Y. Pertsau, A. B. Gourinovitch, D. V. Kupryianava

“…The paper presents an original LANet model for improving medical image segmentation results based on MobileViT neural network. The developed and integrated Efficient Fusion Attention and Adaptive Feature Fusion blocks improve the quality of feature extraction and reduce data redundancy. …”
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Transformer network enhanced by dual convolutional neural network and cross-attention for wheelset bearing fault diagnosis by Jing Zhao, Jing Zhao, Junfeng Li, Ziteng Li, Zengqiang Ma, Zengqiang Ma

“…However, current deep neural networks suffer from design flaws, including low accuracy, high computational complexity, limitations in frequency-domain analysis, and inefficient long time-series feature encoding. …”
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Random forest–based feature selection and detection method for drunk driving recognition by ZhenLong Li, HaoXin Wang, YaoWei Zhang, XiaoHua Zhao

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Improving Recommender Systems for Fake News Detection in Social Networks with Knowledge Graphs and Graph Attention Networks by Aleksei Golovin, Nataly Zhukova, Radhakrishnan Delhibabu, Alexey Subbotin

“…This paper addresses the pervasive problem of fake news propagation in social networks. Traditional text-based detection models often suffer from performance degradation over time due to their reliance on evolving textual features. …”
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