AI-driven video summarization for optimizing content retrieval and management through deep learning techniques by Deepali Vora, Payal Kadam, Dadaso D Mohite, Nilesh Kumar, Nimit Kumar, Pratheeik Radhakrishnan, Shalmali Bhagwat

“…To address these limitations, a novel approach is proposed, where convolutional neural networks and long short-term memory networks are utilized to extract both frame-level and temporal video features. …”
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Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance With EDA and Multi-Channel CNN by Komang Wahyu Trisna, Jinjie Huang, Yuanjian Chen, I Gede Juliana Eka Putra

“…In this study, we propose a novel framework dynamic Easy Data Augmentation (EDA) technique with a Multi-Channel Convolutional Neural Network (MCNN) to address these issues. …”
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3D fault detection method using TransVNet by Yang Lei, Chenqiang Zhang, Wenjing Wu, Mingchun Chen, Mingchun Chen, Xiaotao Wen, Xilei He, Chenggang Bai, Siping Qin, Ying Li, Lijing Wang

“…However, the accuracy and continuity of predictions generated by existing convolutional neural networks (CNNs) on real seismic data fail to meet practical production requirements.MethodsTo address this issue, we integrated the Transformer architecture into the V-Net framework, proposing a fault detection method based on the TransVNet network. …”
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Attention-Guided Sample-Based Feature Enhancement Network for Crowded Pedestrian Detection Using Vision Sensors by Shuyuan Tang, Yiqing Zhou, Jintao Li, Chang Liu, Jinglin Shi

“…To address this, we introduce a novel architecture termed the Attention-Guided Feature Enhancement Network (AGFEN), designed within the deep convolutional neural network framework. AGFEN improves the semantic information of high-level features by mapping it onto low-level feature details through sampling, creating an effect comparable to mask modulation. …”
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Fidex and FidexGlo: From Local Explanations to Global Explanations of Deep Models by Guido Bologna, Jean-Marc Boutay, Damian Boquete, Quentin Leblanc, Deniz Köprülü, Ludovic Pfeiffer

“…Both algorithms generate explanations by means of propositional rules. In our framework, the discriminative boundaries are parallel to the input variables and their location is precisely determined. …”
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Gas concentration prediction in photoacoustic spectroscopy using PSO-EAP-CNN to address correlation degradation by Zhanshang Su, Pengpeng Wang, Zhengzhuo Li, Yawen Li, Tianxiang Zhao, Yujie Duan, Fupeng Wang, Cunguang Zhu

“…The proposed framework employs a multi-scale feature extraction mechanism through its convolutional architecture, while simultaneously optimizing network parameters via PSO, thereby achieving accelerated convergence and improved prediction stability. …”
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Multi-Stage Neural Network-Based Ensemble Learning Approach for Wheat Leaf Disease Classification by Samia Nawaz Yousafzai, Inzamam Mashood Nasir, Sara Tehsin, Dania Saleem Malik, Ismail Keshta, Norma Latif Fitriyani, Yeonghyeon Gu, Muhammad Syafrudin

“…The various stages in the EL approach employ a multi-level framework to enhance feature extraction and capture complex data patterns. …”
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Infrared radiometric image classification and segmentation of cloud structures using a deep-learning framework from ground-based infrared thermal camera observations by K. Sommer, W. Kabalan, R. Brunet

“…In this work, we propose a new complete deep-learning framework to perform image classification and segmentation with convolutional neural networks. …”
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A Synergistic CNN-DF Method for Landslide Susceptibility Assessment by Jiangang Lu, Yi He, Lifeng Zhang, Qing Zhang, Jiapeng Tang, Tianbao Huo, Yunhao Zhang

“…Deep forest (DF) is a decision tree-based DL framework that uses a cascade structure to process features, with model depth adapting to the input data. …”
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WGCAMNet: Wasserstein Generative Adversarial Network Augmented and Custom Attention Mechanism Based Deep Neural Network for Enhanced Brain Tumor Detection and Classification by Fatema Binte Alam, Tahasin Ahmed Fahim, Md Asef, Md Azad Hossain, M. Ali Akber Dewan

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Renal Biopsy Pathological Tissue Segmentation: A Comprehensive Review and Experimental Analysis by Yan Liu, Taiping Wang, Xinxin He, Wei Wang, Qiang He, Juan Jin

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Channel-Dependent Multilayer EEG Time-Frequency Representations Combined with Transfer Learning-Based Deep CNN Framework for Few-Channel MI EEG Classification by Ziang Liu, Kang Fan, Qin Gu, Yaduan Ruan

“…By adopting a deep convolutional neural network with EfficientNet as the backbone and utilizing pre-trained weights from natural image datasets for transfer learning, the framework can simultaneously learn temporal, spatial, and channel features embedded in the CDML-EEG-TFR. …”
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End-to-End Stroke Imaging Analysis Using Effective Connectivity and Interpretable Artificial Intelligence by Wojciech Ciezobka, Joan Falco-Roget, Cemal Koba, Alessandro Crimi

“…This transparent analytical framework not only enhances clinical interpretability but also instills confidence in decision-making processes, crucial for translating research findings into clinical practice. …”
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SCASNet: Spatial Context-Aware Selection Network for Small Object Detection in Aerial Imagery by Zhenkuan Wang, Xue-Mei Dong, Yongli Xu

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A Framework for Early Detection of Acute Lymphoblastic Leukemia and Its Subtypes From Peripheral Blood Smear Images Using Deep Ensemble Learning Technique by Sajida Perveen, Abdullah Alourani, Muhammad Shahbaz, M. Usman Ashraf, Isma Hamid

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Cloud-based optimized deep learning framework for automated glaucoma detection using stationary wavelet transform and improved grey-wolf-optimization with ELM approach by Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, Anuradha S. Kanade, Mohammad Shameem, Harendra S. Jangwan, P.M. Ashok Kumar, Abu Taha Zamani

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Embedded Artificial Intelligence for IoT Applications Using the MAX78000 by Martina Balbi, Lance Doherty, Thomas Watteyne

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Video Analysis and Frame Prediction Based on Improved Object Detection and ConvGRU by Xijuan Wang, Ru Chen

“…Comparative models included future frame prediction models based on generative auxiliary discrimination networks, multi-source prediction frameworks based on spherical convolution, and inverted pyramid prediction models based on cross-optical flow registration. …”
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FE-SKViT: A Feature-Enhanced ViT Model with Skip Attention for Automatic Modulation Recognition by Guangyao Zheng, Bo Zang, Penghui Yang, Wenbo Zhang, Bin Li

“…This innovative design adeptly harnesses the advantages of translation variant convolution and the Transformer framework, handling intra-signal variance and small cross-signal variance to achieve enhanced recognition accuracy. …”
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Evaluating soil erosion zones in the Kangsabati River basin using a stacking framework and SHAP model: a comparative study of machine learning approaches by Javed Mallick, Saeed Alqadhi, Swapan Talukdar, Md Nawaj Sarif, Tania Nasrin, Hazem Ghassan Abdo

“…This study aimed to predict soil erosion susceptibility zones in the basin using integrated soil erosion and deep learning (DL) based stacking framework. Additionally, the SHAP (SHapley Additive exPlanations) model was utilized to augment the interpretability of the DL model. …”
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