Application of convolutional neural networks in the intelligence security system subsystem by V. S. Demeshko, A. I. Фёдоров

“…Training and verification of the recognition quality of architecture data was carried out on an experimentally created data set with a human image on a contrasting background and at different ranges. …”
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Application of a conditional generative adversarial network to denoising solar observations by Md Mushfiqur Rahman, Harry P. Warren

“…Unfortunately, after being in operation since 2006, the EIS detectors have become noisy, which poses a challenge to data analysis. This paper presents a Conditional Generative Adversarial Network (cGAN) tailored to address the unique noise characteristics inherent in EIS data over the mission. …”
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Design of a Classification Recognition Model for Bone and Muscle Anatomical Imaging Based on Convolutional Neural Network and 3D Magnetic Resonance by Ting Pan, Yang Yang

“…In this paper, we use convolutional neural networks to conduct in-depth research and analysis on the classification and recognition of bone and muscle anatomical imaging graphics of 3D magnetic resonance and design corresponding models for practical applications. …”
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Benchmarking Deep Learning for Wetland Mapping in Denmark Using Remote Sensing Data by Muhammad Rizwan Asif

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Deep Learning for Glioblastoma Multiforme Detection from MRI: A Statistical Analysis for Demographic Bias by Kebin Contreras, Julio Gutierrez-Rengifo, Oscar Casanova-Carvajal, Angel Luis Alvarez, Patricia E. Vélez-Varela, Ana Lorena Urbano-Bojorge

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Semi-supervised tissue segmentation from histopathological images with consistency regularization and uncertainty estimation by G. V. S. Sudhamsh, S. Girisha, R. Rashmi

“…Deep learning, particularly Convolutional Neural Networks (CNNs), offers the ability to automate this procedure by recognizing patterns in tissue images. …”
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Development of Bimodal Emotion Recognition System Based on Skin Temperature and Heart Rate Variability Using Hybrid Neural Networks by Sayat Orynbassar, Duygun Erol Barkana, Evan Yershov, Madiyar Nurgaliyev, Ahmet Saymbetov, Batyrbek Zholamanov, Gulbakhar Dosymbetova, Ainur Kapparova, Nursultan Koshkarbay, Nurzhigit Kuttybay, Askhat Bolatbek, Kymbat Kopbay, Dinara Almen

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Advancing EMC Analysis With GAN-Driven Signal Classification and Waveform Modulation by Mona Esmaeili, Sameer D. Hemmady, Oameed Noakoasteen, Edl Schamiloglu, Christos Christodoulou, Payman Zarkesh-Ha

“…By leveraging a Generative Adversarial Network (GAN) trained on ‘safe’ and ‘unsafe’ signal images, our system can effectively recognize and distinguish between these two states. …”
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Advancements in Landmine Detection: Deep Learning-Based Analysis With Thermal Drones by Daniel Heuschmid, Oliver Wacker, Yannick Zimmermann, Pascal Penava, Ricardo Buettner

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Evaluation of CNN-Based Approaches to Adverse Weather Image Classification for Autonomous Driving Systems by Viktoria Afxentiou, Tanya Vladimirova

“…This paper introduces a novel evaluation methodology for classifying AWC images using Convolutional Neural Network (CNN) models, with the goal of assessing their effectiveness for use in ADSs. …”
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Diagnostic accuracy of convolutional neural networks in classifying hepatic steatosis from B-mode ultrasound images: a systematic review with meta-analysis and novel validation in... by Akshay Jagadeesh, Chanchanok Aramrat, Santosh Rai, Fathima Hana Maqsood, Adarsh Kibballi Madhukeshwar, Santhi Bhogadi, Judith Lieber, Hemant Mahajan, Santosh Kumar Banjara, Alexandra Lewin, Sanjay Kinra, Poppy Mallinson

“…Methods: We systematically reviewed two biomedical databases up to Dec 12, 2023, to identify studies that applied CNNs in the classification of HS using B-mode ultrasound images as input (PROSPERO: CRD42024501483). We supplemented this review with a novel analysis of the community-based Andhra Pradesh Children and Parents’ Study (APCAPS) in India to address the overrepresentation of hospital samples and lack of data on South Asian populations who exhibit a distinct central adiposity phenotype that could influence CNN performance. …”
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SPPMFN: Efficient Multimodal Financial Time-Series Prediction Network With Self-Supervised Learning by Ningxin Li, Gang Chao, Jianke Zou, Gaozhe Jiang

“…Financial time series exhibit high volatility and non-linearity, making analysis particularly challenging. Traditional statistical methods like ARIMA and GARCH struggle with non-linear data. …”
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An Improved Convolutional Neural Network (CNN) for Disease Detection and Diagnosis for Multi-crop Plants by Florence Choong Chiao Mei, Bryan Ng Jan Hong

“…Finally, the completed model is saved, and the data obtained is transferred to a cloud network using wireless sensor networks. …”
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Water availability forecasting for Naryn River using ground-based and satellite snow cover data by O. Y. Kalashnikova, A. A. Gafurov

“…The representative mete‑ orological stations with ground‑based observations of snow cover were identified and regression analysis between mean discharge for the vegetation period and number of snow covered days, maximum snow depth based on in‑situ data as well as snow cover area based on MODIS images was conducted. …”
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BlockDroid: detection of Android malware from images using lightweight convolutional neural network models with ensemble learning and blockchain for mobile devices by Emre Şafak, İbrahim Alper Doğru, Necaattin Barışçı, İsmail Atacak

“…By converting Android DEX files into image data, BlockDroid leverages the superior image analysis capabilities of CNN models to discern patterns indicative of malware. …”
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Classifying age from medial clavicle using a 30-year threshold: An image analysis based approach. by Nela Ivković, Željana Bašić, Ivan Jerković

“…A sample was divided into a training (164 images) and testing (40 images) dataset. The images were loaded into the Orange Data Mining 3.32.0., and transformed into vectors using the pre-trained neural network Painters: A model trained to predict painters from artwork images. …”
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Estimation of physico-chemical properties of soil using machine learning by Patience Chizoba Mba, Opegbemi Matthias Busoye, John Temitope Ajayi, Judith Nkechinyere Njoku, Cosmas Ifeanyi Nwakanma, Senorpe Asem-Hiablie, Rammohan Mallipeddi, Tusan Park, Daniel Dooyum Uyeh

“…The study integrated Machine Learning (ML) and Deep Learning (DL) techniques with soil image analysis, employing image feature extraction through Gray-Level Co-occurrence Matrix (GLCM) and Gabor filters to enhance the feature space across 1,388 samples (each consisting of 600 g of soil) and 16 properties. …”
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Computer vision digitization of smartphone images of anesthesia paper health records from low-middle income countries by Ryan D. Folks, Bhiken I. Naik, Donald E. Brown, Marcel E. Durieux

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Digital imaging and vision analysis in science project improves the self-efficacy and skill of undergraduate students in computational work. by Tessa Durham Brooks, Raychelle Burks, Erin Doyle, Mark Meysenburg, Tim Frey

“…The program is designed as a community of practice, providing support within a network of learners. The program focus, images as data, provides a compelling 'hook' for participating scholars. …”
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Automated identification of autism spectrum disorder from facial images using explainable deep learning models by El-Sayed Atlam, Khulood O. Aljuhani, Ibrahim Gad, Elsaid Md. Abdelrahim, Ahmed E. Mansour Atwa, Ali Ahmed

“…Addressing these limitations, automated ASD detection through facial image analysis offers a non-invasive, efficient, and scalable alternative. …”
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