Concept of a geoinformation platform for landmines and other explosive objects detection and mapping with UAV by Mykhailo Popov, Sergey Stankevich, Sergey Mosov, Stanislav Dugin, Stanislav Golubov, Artem Andreiev, Artur Lysenko, Ievgen Saprykin

“…Future studies will involve extensive experimental testing and may involve convolutional neural networks (CNN) as a detection mechanism.…”
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Tree Species Detection and Enhancing Semantic Segmentation Using Machine Learning Models with Integrated Multispectral Channels from PlanetScope and Digital Aerial Photogrammetry i... by Arun Gyawali, Mika Aalto, Tapio Ranta

“…The study mainly involved two different objectives: first, tree species detection using the latest version of You Only Look Once (YOLOv12), and second, semantic segmentation (classification) using random forest, Categorical Boosting (CatBoost), and a Convolutional Neural Network (CNN). …”
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Assessing the effect of ensemble learning algorithms and validation approach on estimating forest aboveground biomass: a case study of natural secondary forest in Northeast China by Hungil Jin, Yinghui Zhao, Unil Pak, Zhen Zhen, Kumryong So

“…This study highlights the potential challenges of applying a leave-one-out cross-validation approach and provides a scientific foundation for the feasibility of different ensemble learning algorithms and cross-validation approaches for accurate AGB estimation.…”
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Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur, Gurjit S. Randhawa, Farhat Abbas, Mumtaz Ali, Travis J. Esau, Aitazaz A. Farooque, Rajandeep Singh

“…A comprehensive review of literature has been conducted by examining over 400 articles to focus on 72 studies including 14 reviews publications on ML and DL models about potato disease forecasting using different techniques. It highlights the need for proficient disease control by integrating image and climate data. …”
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Automatic Identification of Amharic Text Idiomatic Expressions Using a Deep Learning Approach by Habtamu Hunegnaw Limenih, Abebe Belay Adege, Abrham Yaregal Alene, Habtamu Tariku Demasu, Habtamu Molla Belachew

“…Developing a model to identify Amharic idiomatic terms is helpful for different NLP applications like machine translation, sentiment analysis, spam classification, intent recognition, and so on. …”
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Universal conditional networks (UniCoN) for multi-age embryonic cartilage segmentation with sparsely annotated data by Nishchal Sapkota, Yejia Zhang, Zihao Zhao, Maria Jose Gomez, Yuhan Hsi, Jordan A. Wilson, Kazuhiko Kawasaki, Greg Holmes, Meng Wu, Ethylin Wang Jabs, Joan T. Richtsmeier, Susan M. Motch Perrine, Danny Z. Chen

“…While DL approaches have been proposed to automate cartilage segmentation, most such models have limited accuracy and generalizability, especially across data from different embryonic age groups. To address these limitations, we propose novel DL methods that can be adopted by any DL architectures—including Convolutional Neural Networks (CNNs), Transformers, or hybrid models—which effectively leverage age and spatial information to enhance model performance. …”
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Enhancing Cross-Domain Remote Sensing Scene Classification by Multi-Source Subdomain Distribution Alignment Network by Yong Wang, Zhehao Shu, Yinzhi Feng, Rui Liu, Qiusheng Cao, Danping Li, Lei Wang

“…First, it includes a pre-trained convolutional neural network (CNN) as a common feature extractor to fully exploit the shared invariant features across one target and multiple source domains. …”
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EBSSPA: Efficient Deep Learning Model for Enhancing Blockchain Scalability and Security Through Fusion Pattern Analysis by Anuradha Hiwase, Amit Pimpalkar, Barkha Dange, Nitin Thakre, Sakshi Jaiswal, Tejaswini Mankar

“…Background: Blockchain technologies have come a long way, and integration of blockchain technologies into different fields is flourishing; however, there is a lack of blockchain platforms to manage the high network loads and more sophisticated security threats. …”
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Controlled and Real-Life Investigation of Optical Tracking Sensors in Smart Glasses for Monitoring Eating Behavior Using Deep Learning: Cross-Sectional Study by Simon Stankoski, Ivana Kiprijanovska, Martin Gjoreski, Filip Panchevski, Borjan Sazdov, Bojan Sofronievski, Andrew Cleal, Mohsen Fatoorechi, Charles Nduka, Hristijan Gjoreski

“…ResultsStatistical tests of mean sensor activations revealed statistically significant differences across all 6 comparison pairs (P<.001) involving 2 sensors (cheeks and temple) and 3 facial activities (eating, clenching, and speaking). …”
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Traffic environment perception algorithm based on multi-task feature fusion and orthogonal attention by Zhengfeng LI, Mingen ZHONG, Yihong ZHANG, Kang FAN, Zhiying DENG, Jiawei TAN

“…By integrating features across different scales, C2f-K effectively reduces background noise and interference, thereby improving the understanding of complex scenes of the model. …”
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Machine learning to identify suitable boundaries for band-pass spectral analysis of dynamic [ $$^{11}$$ 11 C]Ro15-4513 PET scan and voxel-wise parametric map generation by Zeyu Chang, Colm J. McGinnity, Rainer Hinz, Manlin Wang, Joel Dunn, Ruoyang Liu, Mubaraq Yakubu, Paul Marsden, Alexander Hammers

“…Parametric maps applying different boundaries for different ROIs were generated. …”
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A Method of Image Restoration for Distortion of Object in Water-Air Cross-Media by Yuhe Gao, Jishen Jia, Lei Cai, Meng Zhou, Haojie Chai, Jinze Jia

“…To address these issues, this paper proposes a repair network to correct object image distortion in water-air cross-media. Firstly, convolutional combination performs feature extraction on water-air cross-media images, which retains the same features at the same scale and marks feature points with large differences. …”
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Research on Data Repair of Pile-Type Adjustable Wind Turbine Foundation Monitoring Based on FST-ATTNet by WEI Huanwei, ZHAO Jizhang, ZHENG Xiao, TAN Fang, LIU Cong

“…In the spatial domain, the Temporal Convolutional Network (TCN) models long-range dependencies by expanding causal convolutions, thereby capturing local and global spatial relationships. …”
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Mock Observations: Morphological Analysis of Galaxies in TNG100 Simulations by Jun-Yu Gong, Weipeng Lin, Lin Tang, Yanyao Lan

“…Our findings show that the morphological characteristics of the mock-observed galaxy samples closely match those observed in the SDSS, successfully reproducing key features such as distinct parameter distributions for different types. However, some discrepancies are identified: notably, a significant lack of early-type galaxies (ETGs) in the dwarf galaxy regime ( M _* < 10 ^10 M _⊙ ) and minimal distinction between Sab/Sb and Sc/Sd/irregular galaxies in the mock-observed samples, unlike the clear differences seen in actual observations. …”
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DOA Estimation Based on CNNs Embedded With Mamba by Zhang Ziyan, Yi Shichao, Wang Chengyi

“…The convolutional neural networks (CNN) have been proved to be more efficient in Direction of Arrival (DOA) estimation of underwater acoustic array signals. …”
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The role of learned song in the evolution and speciation of Eastern and Spotted towhees. by Ximena León Du'Mottuchi, Nicole Creanza

“…Here, we quantify 16 song features to analyze geographic variation in Spotted and Eastern towhee songs and assess species-level differences. We then use several machine learning models to measure how accurately their songs can be classified by species. …”
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Degradation prediction of PEM water electrolyzer under constant and start-stop loads based on CNN-LSTM by Boshi Xu, Wenbiao Ma, Wenyan Wu, Yang Wang, Yang Yang, Jun Li, Xun Zhu, Qiang Liao

“…However, it is difficult to establish a mechanism model incorporating all degradation categories due to their different time and spatial scales. In this paper, the data-driven method is employed to predict the electrolyzer voltage variation over time based on a convolutional neural network-long short term memory (CNN-LSTM) model. …”
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Combining UAV Multispectral and Thermal Infrared Data for Maize Growth Parameter Estimation by Xingjiao Yu, Xuefei Huo, Long Qian, Yiying Du, Dukun Liu, Qi Cao, Wen’e Wang, Xiaotao Hu, Xiaofei Yang, Shaoshuai Fan

“…This study explores the integration of UAV-based multispectral (MS) and thermal infrared (TIR) data to improve the estimation of maize LAI and LCC across different growth stages, aiming to enhance nitrogen (N) management. …”
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A Novel Short‐Term Prediction Model for Regional Equatorial Plasma Bubble Irregularities in East and Southeast Asia by Xiukuan Zhao, Guozhu Li, Haiyong Xie, Lianhuan Hu, Wenjie Sun, Yi Li, Guofeng Dai, Jianfei Liu, Yu Li, Baiqi Ning, Michi Nishioka, Septi Perwitasari, Prasert Kenpankho

“…The spatial and temporal distributions of EPB irregularities, including their latitudinal variation and delayed onset after sunset, and the occurrence across different days in East and Southeast Asia, were well predicted by the STEP. …”
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A Dual-Technology Approach: Handheld NIR Spectrometer and CNN for <i>Fritillaria</i> spp. Quality Control by Fengling Li, Wen Lei, Juan Li, Xiaoting Wang, Jingyu Su, Tangnuer Sahati, Xiahenazi Aierkenjiang, Ruyi Tian, Weihong Zhou, Jixiong Zhang, Jingjing Xia

“…<i>Fritillaria</i> spp. has an extremely high edible and medicinal value. Different parts of it exhibit significant variations in medicinal efficacy. …”
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