Improving Road Semantic Segmentation Using Generative Adversarial Network by Arnick Abdollahi, Biswajeet Pradhan, Gaurav Sharma, Khairul Nizam Abdul Maulud, Abdullah Alamri

“…Comparisons demonstrate that the proposed GAN framework outperforms prior CNN-based approaches and is particularly effective in preserving edge information.…”
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TMS: Ensemble Deep Learning Model for Accurate Classification of Monkeypox Lesions Based on Transformer Models with SVM by Elsaid Md. Abdelrahim, Hasan Hashim, El-Sayed Atlam, Radwa Ahmed Osman, Ibrahim Gad

“…Conclusions: The results of the study show that the proposed hybrid framework achieves robust diagnostic performance in monkeypox detection, offering potential utility for enhanced disease monitoring and outbreak management. …”
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MDFT-GAN: A Multi-Domain Feature Transformer GAN for Bearing Fault Diagnosis Under Limited and Imbalanced Data Conditions by Chenxi Guo, Vyacheslav V. Potekhin, Peng Li, Elena A. Kovalchuk, Jing Lian

“…To address these challenges, this paper proposes a novel fault diagnosis framework based on a Multi-Domain Feature Transformer GAN (MDFT-GAN). …”
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A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

“…However, most of these extrapolation network architectures are built upon convolutional neural networks, using radar echo images as input. …”
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An Unsupervised Learning Method for Radio Interferometry Deconvolution by Lei Yu, Bin Liu, Cheng-Jin Jin, Ru-Rong Chen, Hong-Wei Xi, Bo Peng

“…Building on this insight, we develop a deep dictionary (realized through a convolutional neural network), which is designed to be multiresolution and overcomplete, to achieve sparse representation and integrate it within the CS framework. …”
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Quality-Aware PPG-Based Blood Pressure Classification for Energy-Efficient Trustworthy BP Monitoring Devices With Reduced False Alarms by Yalagala Sivanjaneyulu, M. Sabarimalai Manikandan, Srinivas Boppu, Linga Reddy Cenkeramaddi

“…The proposed framework includes a high-pass filter (HPF), PPG signal quality assessment (PPG-SQA), PPG waveform feature extraction (FE), and BP classification (hypertension and non-hypertension (NHT)). …”
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Synthesizing field plot and airborne remote sensing data to enhance national forest inventory mapping in the boreal forest of Interior Alaska by Pratima Khatri-Chhetri, Hans-Erik Andersen, Bruce Cook, Sean M. Hendryx, Liz van Wagtendonk, Van R. Kane

“…In this study, we present a framework for forest type classification combining field plots and high-resolution remote sensing data using machine learning models in the boreal forest of Interior Alaska. …”
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Application of deep learning for diagnosis of shoulder diseases in older adults: a narrative review by Sung Min Rhee

“…Recent research highlights the effectiveness of DL-based convolutional neural networks and machine learning frameworks in diagnosing various shoulder pathologies. …”
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Use of Artificial Intelligence in Imaging Dementia by Manal Aljuhani, Azhaar Ashraf, Paul Edison

“…Artificial intelligence algorithms (machine learning and deep learning) enable automation of neuroimaging interpretation and may reduce potential bias and ameliorate clinical decision-making. Graph convolutional network-based frameworks implicitly provide multimodal sparse interpretability to support the detection of Alzheimer’s disease and its prodromal stage, mild cognitive impairment. …”
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Hybrid Reinforcement Learning-Based Collision Avoidance Algorithm for Autonomous Vehicle Clusters by Chubing Guo, Jianshe Wu, Panzheng Luo, Zhigang Wang, Kai Zhang, Ziyi Yang, Zengfa Dou, Kan Song

“…A hybrid reinforcement learning framework is designed, which consists of a deep neural network structure and a reinforcement learning structure. …”
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Validation of Replicable Pipeline 3D Surface Reconstruction for Patient-Specific Abdominal Aortic Lumen Diagnostics by Edoardo Ugolini, Giorgio La Civita, Moad Al Aidroos, Samuele Salti, Giuseppe Lisanti, Emanuele Ghedini, Gianluca Faggioli, Mauro Gargiulo, Giovanni Rossi

“…The goal is to provide a solid tool for geometric reconstruction to a more complex enhanced diagnostic framework. <b>Methods:</b> A U-Net convolutional neural network is trained using preoperative CTA scans, with 101 for model training and 14 for model testing, covering a wide anatomical and aortoiliac pathology spectrum. …”
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Explainable Siamese Neural Networks for Detection of High Fall Risk Older Adults in the Community Based on Gait Analysis by Christos Kokkotis, Kyriakos Apostolidis, Dimitrios Menychtas, Ioannis Kansizoglou, Evangeli Karampina, Maria Karageorgopoulou, Athanasios Gkrekidis, Serafeim Moustakidis, Evangelos Karakasis, Erasmia Giannakou, Maria Michalopoulou, Georgios Ch Sirakoulis, Nikolaos Aggelousis

“…Methods: By leveraging convolutional neural networks (CNNs) and Siamese neural networks (SNNs), the proposed framework effectively addresses the challenges of limited datasets and delivers robust predictive capabilities. …”
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Detection of microfibres in wastewater sludge with deep learning by Félix Martí-Pérez, Ana Domínguez-Rodríquez, Carlos Monserrat, Cèsar Ferri, María-José Luján-Facundo, Eva Ferrer-Polonio, Amparo Bes-Piá, José-Antonio Mendoza-Roca

“…Our deep learning framework, implemented using Mask R-CNN architecture, demonstrates superior performance in detecting MFi, achieving a mean average precision (mAP) of 72% for the glass dataset and 68% for the cellulose acetate dataset. …”
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Truth be told: a multimodal ensemble approach for enhanced fake news detection in textual and visual media by Rami Mohawesh, Islam Obaidat, Ahmed Abdallah AlQarni, Ali Abdulaziz Aljubailan, Moy’awiah A. Al-Shannaq, Haythem Bany Salameh, Ali Al-Yousef, Ahmad A. Saifan, Suboh M. Alkhushayni, Sumbal Maqsood

“…This paper presents (Verifiable Fake News Detection), a framework tailored to detect fake news in articles that incorporate both textual and visual content. employs a multi-modal ensemble approach, an integration technique that combines various models and data sources for a holistic analysis, to aggregate feature vectors from different media sources within a news article and effectively classify its credibility. …”
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A Human-Centric, Uncertainty-Aware Event-Fused AI Network for Robust Face Recognition in Adverse Conditions by Akmalbek Abdusalomov, Sabina Umirzakova, Elbek Boymatov, Dilnoza Zaripova, Shukhrat Kamalov, Zavqiddin Temirov, Wonjun Jeong, Hyoungsun Choi, Taeg Keun Whangbo

“…A custom hybrid backbone that couples convolutional networks with transformers keeps the model nimble enough for edge devices. …”
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DANNET: deep attention neural network for efficient ear identification in biometrics by Deepthy Mary Alex, Kalpana Chowdary M., Hanan Abdullah Mengash, Venkata Dasu M., Natalia Kryvinska, Chinna Babu J., Ajmeera Kiran

“…Despite numerous proposed convolutional neural network (CNN) based deep learning techniques for ear detection, achieving the expected efficiency and accuracy remains a challenge. …”
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Application of Image Computing in Non-Destructive Detection of Chinese Cuisine by Xiaowei Huang, Zexiang Li, Zhihua Li, Jiyong Shi, Ning Zhang, Zhou Qin, Liuzi Du, Tingting Shen, Roujia Zhang

“…This study pioneers a hyperspectral imaging framework enhanced with domain-specific deep learning algorithms (spatial–spectral convolutional networks with attention mechanisms) to address these challenges. …”
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StomaYOLO: A Lightweight Maize Phenotypic Stomatal Cell Detector Based on Multi-Task Training by Ziqi Yang, Yiran Liao, Ziao Chen, Zhenzhen Lin, Wenyuan Huang, Yanxi Liu, Yuling Liu, Yamin Fan, Jie Xu, Lijia Xu, Jiong Mu

“…Leveraging the YOLOv11 framework, StomaYOLO integrates the Small Object Detection layer P2, the dynamic convolution module, and exploits large-scale epidermal cell features to enhance stomatal recognition through auxiliary training. …”
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ST-YOLOv8: Small-Target Ship Detection in SAR Images Targeting Specific Marine Environments by Fei Gao, Yang Tian, Yongliang Wu, Yunxia Zhang

“…To achieve this goal, we propose several architectural improvements to You Only Look Once version 8 Nano (YOLOv8n) and present Small Target-YOLOv8(ST-YOLOv8)—a novel lightweight SAR ship detection model based on the enhance YOLOv8n framework. The C2f module in the backbone’s transition sections is replaced by the Conv_Online Reparameterized Convolution (C_OREPA) module, reducing convolutional complexity and improving efficiency. …”
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Artificial Intelligence for Multiclass Rhythm Analysis for Out-of-Hospital Cardiac Arrest During Mechanical Cardiopulmonary Resuscitation by Iraia Isasi, Xabier Jaureguibeitia, Erik Alonso, Andoni Elola, Elisabete Aramendi, Lars Wik

“…The aim of this study was to design a deep learning (DL)-based framework for cardiac automatic multiclass rhythm classification in the presence of CC artifacts during OHCA. …”
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