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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Mitigating Cyber Risks in Smart Cyber-Physical Power Systems Through Deep Learning and Hybrid Security Models by M. A. S. P. Dayarathne, M. S. M. Jayathilaka, R. M. V. A. Bandara, V. Logeeshan, S. Kumarawadu, Chathura Wanigasekara

“…By incorporating a novel pre-processing method that leverages feature derivatives, the proposed models achieve over 98% accuracy in detecting cyber threats, providing a robust framework for protecting smart power grids from evolving cyber risks.…”
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WindDefNet: A Multi-Scale Attention-Enhanced ViT-Inception-ResNet Model for Real-Time Wind Turbine Blade Defect Detection by Majad Mansoor, Xiyue Tan, Adeel Feroz Mirza, Tao Gong, Zhendong Song, Muhammad Irfan

“…This work introduces an enhanced deep learning-based framework for real-time detection of wind turbine blade defects. …”
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The integration of artificial intelligence in assisted reproduction: a comprehensive review by Pragati Kakkar, Shruti Gupta, Kasmiria Ioanna Paschopoulou, Ilias Paschopoulos, Ioannis Paschopoulos, Vassiliki Siafaka, Orestis Tsonis

“…AI's capacity for precise image-based analysis, leveraging convolutional neural networks, stands out as a promising avenue. …”
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AI-Driven UAV Surveillance for Agricultural Fire Safety by Akmalbek Abdusalomov, Sabina Umirzakova, Komil Tashev, Nodir Egamberdiev, Guzalxon Belalova, Azizjon Meliboev, Ibragim Atadjanov, Zavqiddin Temirov, Young Im Cho

“…In this study, we propose an advanced deep learning-based fire-detection framework that integrates the Single-Shot MultiBox Detector (SSD) with the computationally efficient MobileNetV2 architecture. …”
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CABAD: A video dataset for benchmarking child aggression recognition by Shehzad Ali, Md Tanvir Islam, Ik Hyun Lee, Mohammad Hijji, Khan Muhammad

“…Leveraging CABAD, we propose CABA_Net, a multi-stage deep-learning framework integrating MobileViT for spatial feature extraction, Temporal Convolutional Networks (TCN) for sequential modeling, and an Attention LSTM for refined temporal attention on behavioral patterns. …”
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Multimodal Emotion Recognition Based on Facial Expressions, Speech, and EEG by Jiahui Pan, Weijie Fang, Zhihang Zhang, Bingzhi Chen, Zheng Zhang, Shuihua Wang

“…Specifically, the proposed Deep-Emotion framework consists of three branches, i.e., the facial branch, speech branch, and EEG branch. …”
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DCANet: A Dual-Branch Cross-Scale Feature Aggregation Network for Remote Sensing Image Semantic Segmentation by Yanhong Yang, Fei Wang, Haozheng Zhang, Yushan Xue, Guodao Zhang, Shengyong Chen

“…In this article, we introduce DCANet, a dual-branch cross-scale feature aggregation network based on an encoder–decoder framework, incorporating visual-state-space (VSS) blocks in the encoder branch to overcome the limitations of conventional convolutional neural networks in capturing global contextual information. …”
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HAMF: A Novel Hierarchical Attention-Based Multi-Modal Fusion Model for Parkinson’s Disease Classification and Severity Prediction by Anitha Rani Palakayala, P. Kuppusamy, D. Kothandaraman, Gunakala Archana, Jaideep Gera

“…A comprehensive approach is a multi-modal framework that overcomes these limitations by integration of brain Magnetic Resonance Imaging (MRI) data, gait analysis, and speech signals for enhanced classification and severity estimation of PD. …”
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Enhancing Lung Cancer Detection through Dual Imaging Modality Integration by Costin Teodor STREBA, Mircea-Sebatian ŞERBĂNESCU, Liliana STREBA, Alin Dragoş DEMETRIAN, Andreea-Georgiana GHEORGHE, Mădălin MĂMULEANU, Daniel-Nicolae PIRICI

“…By integrating histological and pCLE imaging, the dual TL framework significantly improves classification accuracy for lung cancer detection, making it a promising technique for further developments. …”
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Deep Learning-Based Detection and Digital Twin Implementation of Beak Deformities in Caged Layer Chickens by Hengtai Li, Hongfei Chen, Jinlin Liu, Qiuhong Zhang, Tao Liu, Xinyu Zhang, Yuhua Li, Yan Qian, Xiuguo Zou

“…Additionally, the standard convolutional blocks in the neck of the original model were replaced with Grouped Shuffle Convolution (GSConv) modules, effectively reducing information loss during feature extraction. …”
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Robust Image Steganography Approach Based on Edge Detection Combined With CNN Algorithm by Rana Al-Rawashdeh, Md Mahfuzur Rahman, Mahmood Niazi

“…In this research, a new framework is proposed that integrates the edge detection strategy (using edge detectors) with the deep learning methods, such as a convolutional neural network (CNN), for making secret data embedding and extraction processes efficient. …”
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Construction and application of foundational models for intelligent processing of microseismic events in mines by Anye CAO, Maotao LI, Xu YANG, Yao YANG, Sen LI, Yaoqi LIU, Changbin WANG

“…This technological breakthrough establishes a robust framework for intelligent monitoring and precise early warning of mine dynamic disasters, effectively overcoming the limitations of traditional methods in complex geological environments.…”
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