Explainable clinical diagnosis through unexploited yet optimized fine-tuned ConvNeXt Models for accurate monkeypox disease classification by Muhammad Waqar, Zeshan Aslam Khan, Shanzey Tariq Khawaja, Naveed Ishtiaq Chaudhary, Saadia Khan, Khalid Mehmood Cheema, Muhammad Farhan Khan, Syed Sohail Ahmed, Muhammad Asif Zahoor Raja

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A bird song detector for improving bird identification through deep learning: A case study from Doñana by Alba Márquez-Rodríguez, Miguel Ángel Mohedano-Munoz, Manuel J. Marín-Jiménez, Eduardo Santamaría-García, Giulia Bastianelli, Pedro Jordano, Irene Mendoza

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Optimizing Fingerprint Identification: CNNs With Raw Images Versus Handcrafted Features for Real-Time Systems by Shaik Salma, Tauheed Ahmed, Garimella Ramamurthy

“…Despite progress, existing systems still face challenges with noise, database differences, and real-time speed. This study investigates the balance between accuracy and computational efficiency(thereby speed) by comparing two approaches: training a Convolutional Neural Network (CNN) with raw fingerprint images and training a CNN using handcrafted fingerprint features. …”
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Text analysis of DNS queries for data exfiltration protection of computer networks by Ya. V. Bubnov, N. N. Ivanov

“…The paper proposes a method of detecting such DNS requests based on text classification of domain names by convolutional neural network. The efficiency of the method is based on assumption that domain names exploited for data exfiltration differ from domain names formed from words of natural language. …”
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Development of low-cost portable spectrometer equipped with 18-band spectral sensors using deep learning model for evaluating moisture content of rubber sheets by Amorndej Puttipipatkajorn, Amornrit Puttipipatkajorn

“…During testing of the instrument, the results indicated that its predictive performance did not differ significantly from that of the primary calibration model. …”
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Metric learning unveiling disparities: A novel approach to recognize false trigger images in wildlife monitoring by Rui Zhu, Enting Zhao, Chunhe Hu, Jiangjian Xie, Junguo Zhang, Huijian Hu

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Deep Learning Network Selection and Optimized Information Fusion for Enhanced COVID-19 Detection: A Literature Review by Olga Adriana Caliman Sturdza, Florin Filip, Monica Terteliu Baitan, Mihai Dimian

“…However, progress in COVID-19 detection is hindered by ongoing issues stemming from restricted and non-uniform datasets, as well as domain differences in image standards and complications with both diagnostic overfitting and poor generalization capabilities. …”
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Enhanced Osteoporosis Detection Using Artificial Intelligence: A Deep Learning Approach to Panoramic Radiographs with an Emphasis on the Mental Foramen by Robert Gaudin, Wolfram Otto, Iman Ghanad, Stephan Kewenig, Carsten Rendenbach, Vasilios Alevizakos, Pascal Grün, Florian Kofler, Max Heiland, Constantin von See

“…A total of 250 PRs from three groups (A: osteoporosis group, B: non-osteoporosis group matching A in age and gender, C: non-osteoporosis group differing from A in age and gender) were cropped to the mental foramen region. …”
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Automatic Detection and Calculation of Mining Subsidence in Large-Scale Interferograms With Transformer-CNN Model by Hongdong Fan, Jialin Xin, Tao Lin, Jun Wang

“…Subsequently, the Residual Convolution Block and Swin Transformer Block were adopted as the fundamental building blocks of the model architecture to develop RAUNet, a synergistic network designed for detecting and calculating wide-area mining subsidence zones. …”
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FilletCam AI: A handheld tool for precise fillet color profiling of Atlantic salmon and rainbow trout by Rakesh Ranjan, Harsh Shroff, Kata Sharrer, Scott Tsukuda, Christopher Good

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Interpreting CNN models for musical instrument recognition using multi-spectrogram heatmap analysis: a preliminary study by Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan

“…This task poses significant challenges due to the complexity and variability of musical signals.MethodsIn this study, we employed convolutional neural networks (CNNs) to analyze the contributions of various spectrogram representations—STFT, Log-Mel, MFCC, Chroma, Spectral Contrast, and Tonnetz—to the classification of ten different musical instruments. …”
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Research on series arc fault detection method household loads based on voltage signals by Bin Li, Jiahui Shu, Feifan Cui

“…In addition, additional experiments at different sampling frequencies show that the method has good adaptability, and the identification accuracy has better performance when the sampling frequency is 10 KHZ, which has certain theoretical guiding significance for the development of the series arc fault detection device in the next step.…”
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Evaluation of Similarity of Image Explanations Produced by SHAP, LIME and Grad-CAM by Vladyslav Yavtukhovskyi, Violeta Tretynyk

“…Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. …”
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Vegetation classification in a subtropical region with Sentinel-2 time series data and deep learning by Ming Zhang, Dengqiu Li, Guiying Li, Dengsheng Lu

“…Conv1D model based on one-dimensional convolution, GoogLeNet model based on two-dimensional convolution, and CGNet model which fused Conv1D and GoogLeNet) for vegetation classification, respectively. …”
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Consistency regularization based semi-supervised plant disease recognition by Murat Ilsever, Ipek Baz

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A Multi-Architecture Approach for Offensive Language Identification Combining Classical Natural Language Processing and BERT-Variant Models by Ashok Yadav, Farrukh Aslam Khan, Vrijendra Singh

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Comparative Study of Deep Learning-Based Sentiment Classification by Seungwan Seo, Czangyeob Kim, Haedong Kim, Kyounghyun Mo, Pilsung Kang

“…Specifically, eight deep-learning models, three based on convolutional neural networks and five based on recurrent neural networks, with two types of input structures, i.e., word level and character level, are compared for 13 review datasets, and the classification performances are discussed under different perspectives.…”
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Application of big data and artificial intelligence in visual communication art design by Ailing Zhang

“…This essay proposed the STING algorithm for big data for multi-resolution information clustering in VISCOM art. In addition, the convolutional neural network (CNN) in AI technology was used to identify the conveyed objects or scenes to achieve the purpose of designing art with different characteristics for different scenes and groups of people. …”
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Dual-stream dynamic graph structure network for document-level relation extraction by Yu Zhong, Bo Shen

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Assessment of Deep Neural Network Models for Direct and Recursive Multi-Step Prediction of PM10 in Southern Spain by Javier Gómez-Gómez, Eduardo Gutiérrez de Ravé, Francisco J. Jiménez-Hornero

“…The models were also assessed here for recursive multi-step prediction over different forecast periods in three different situations: background concentration, a strong dust event, and an extreme dust event. …”
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