MSCPUnet: A multi-task neural network for plot-level crop classification in complex agricultural areas by Kedi Fang, Shengwei Zhang, Yongting Han, Lin Yang, Meng Luo, Lu Liu, Qian Zhang, Bo Wang

“…This paper first proposes a novel multi-task neural network, Multi-task Multi-Scale Convolutional Pooling Unet (MSCPUnet), for extracting vector plots. …”
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Accurate estimation of permeability reduction resulted from low salinity water flooding in clay-rich sandstones by Xiaojuan Zhang, Muntadher Abed Hussein, Tarak Vora, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Farzona Alimova, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Ahmad Khalid

“…This work provides a comprehensive, validated, and highly accurate ML framework specifically tailored for predicting complex permeability alterations, offering a superior alternative to conventional approaches and enhancing decision-making in EOR projects.…”
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Enhancing Water Bodies Detection in the Highland and Coastal Zones Through Multisensor Spectral Data Fusion and Deep Learning by Xiaofei Han, Nazih Y. Rebouh, Yasmeen Ahmed, Muhammad Nasar Ahmad, Zainab Tahir, Yahia Said, Ishfaq Gujree

“…This study presents a deep-learning-based semantic segmentation framework that leverages multiband Sentinel-2 imagery for delineating glaciers and coastal lakes. …”
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Predictive performance and uncertainty analysis of ensemble models in gully erosion susceptibility assessment by Congtan Liu, Haoming Fan, Yixuan Wang

“…This study aims to identify the optimal feature datasets and to quantify the uncertainty associated with gully erosion prediction models by developing a novel methodological framework based on ensembles of the three machine learning models: Random Forest (RF), Convolutional Neural Network (CNN), and Transformer models. …”
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Apple Yield Estimation Method Based on CBAM-ECA-Deeplabv3+ Image Segmentation and Multi-Source Feature Fusion by Wenhao Cui, Yubin Lan, Jingqian Li, Lei Yang, Qi Zhou, Guotao Han, Xiao Xiao, Jing Zhao, Yongliang Qiao

“…This study establishes a reliable framework for precise fruit tree image segmentation and early yield estimation, advancing precision agriculture applications.…”
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Use of Deep-Learning Genomics to Discriminate Healthy Individuals from Those with Alzheimer’s Disease or Mild Cognitive Impairment by Lanlan Li, Yeying Yang, Qi Zhang, Jiao Wang, Jiehui Jiang, Alzheimer’s Disease Neuroimaging Initiative

“…The proposed deep-learning genomics (DLG) approach consists of three steps: quality control, coding of single-nucleotide polymorphisms, and classification. The ResNet framework was used for the DLG model, and the results were compared with classifications by simple convolutional neural network structure. …”
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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

“…The results of this study provide a general framework, i.e., a geoinformation platform for landmine detection and mapping. …”
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An explainable AI-driven deep neural network for accurate breast cancer detection from histopathological and ultrasound images by Md. Romzan Alom, Fahmid Al Farid, Muhammad Aminur Rahaman, Anichur Rahman, Tanoy Debnath, Abu Saleh Musa Miah, Sarina Mansor

“…This research introduces the Deep Neural Breast Cancer Detection (DNBCD) model, an explainable AI-based framework that utilizes deep learning methods for classifying breast cancer using histopathological and ultrasound images. …”
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Cloud Detection Challenge-Methods and Results by Alessio Barbaro Chisari, Luca Guarnera, Alessandro Ortis, Wladimiro Carlo Patatu, Bruno Casella, Luca Naso, Giuseppe Puglisi, Vincenzo del Zoppo, Mario Valerio Giuffrida, Sebastiano Battiato

“…This paper details the challenge framework, as well as the methodologies proposed by top-performing teams, offering a comparative evaluation of their effectiveness. …”
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Enhanced Magnetic Resonance Imaging-Based Brain Tumor Classification with a Hybrid Swin Transformer and ResNet50V2 Model by Abeer Fayez Al Bataineh, Khalid M. O. Nahar, Hayel Khafajeh, Ghassan Samara, Raed Alazaidah, Ahmad Nasayreh, Ayah Bashkami, Hasan Gharaibeh, Waed Dawaghreh

“…We evaluate the proposed framework using two publicly accessible brain magnetic resonance imaging (MRI) datasets, each including two and four distinct classes, respectively. …”
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SCCA-YOLO: Spatial Channel Fusion and Context-Aware YOLO for Lunar Crater Detection by Jiahao Tang, Boyuan Gu, Tianyou Li, Ying-Bo Lu

“…In this paper, we propose a novel Spatial Channel Fusion and Context-Aware YOLO (SCCA-YOLO) model built upon the YOLO11 framework. Specifically, the Context-Aware Module (CAM) employs a multi-branch dilated convolutional structure to enhance feature richness and expand the local receptive field, thereby strengthening the feature extraction capability. …”
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The Prediction of Sound Insulation for the Front Wall of Pure Electric Vehicles Based on AFWL-CNN by Yan Ma, Jie Yan, Jianjiao Deng, Xiaona Liu, Dianlong Pan, Jingjing Wang, Ping Liu

“…In response to the limitations of traditional experimental and simulation methods in terms of accuracy and efficiency, this paper proposes a convolutional neural network (AFWL-CNN) based on adaptive weighted feature learning. …”
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Enhancing Anomaly Detection in Attributed Networks Using Proximity Preservation and Advanced Embedding Techniques by Wasim Khan, Mohammad Ishrat, Mohammad Nadeem Ahmed, Shafiqul Abidin, Mohammad Husain, Mohd Izhar, Abu Taha Zamani, Mohammad Rashid Hussain, Arshad Ali

“…To address this, we propose a novel approach that combines a Graph Convolution Auto encoder (GCAE) with self-supervised learning, proximity preservation, and adversarial training using Generative Adversarial Networks (GAN). …”
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Computational methods and artificial intelligence-based modeling of magnesium alloys: a systematic review of machine learning, deep learning, and data-driven design and optimizatio... by Hanxuan Wang, Raman Kumar, Raman Kumar, Ashutosh Pattanaik, Rajender Kumar, Rajender Kumar, Ali Saeed Owayez Khawaf Aljaberi, Mayada Ahmed Abass

“…The review highlights the extensive application of models, including Artificial Neural Networks, Convolutional Neural Networks, and hybrid frameworks that combine ML with optimization algorithms or physical simulations. …”
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Data-driven polarimetric approaches fuel computational imaging expansion by Sylvain Gigan

“…Incorporating polarization in computer vision tasks provides new solutions to high-level analytics, in particular when coupled with machine learning frameworks such as convolutional neural networks (CNN). …”
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Multi-Head Graph Attention Adversarial Autoencoder Network for Unsupervised Change Detection Using Heterogeneous Remote Sensing Images by Meng Jia, Xiangyu Lou, Zhiqiang Zhao, Xiaofeng Lu, Zhenghao Shi

“…Our bidirectional adversarial convolutional autoencoder simultaneously aligns features across both domains. …”
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The analysis of motion recognition model for badminton player movements using machine learning by Xuanmin Zhu, Lizhi Liu, Jingshuo Huang, Genyan Chen, Xi Ling, Yanshuo Chen

“…Abstract This study aims to comprehensively analyze and classify the badminton players’ swing actions by combining the theoretical frameworks of quantum mechanics and machine learning. …”
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Ensemble learning for microbiome-based caries diagnosis: multi-group modeling and biological interpretation from salivary and plaque metagenomic data by Fangqiao Wei, Zailong Wu, Guanghui Li, Xiangyu Sun, Xiangru Shi, Lei Tan, Tianxiang Ai, Long Qu, Shuguo Zheng

“…Conclusion The current work provided reliable diagnostic models for early childhood caries, and established a robust computational framework for AI-driven microbiome analysis. This study, by focusing on the characteristics of the oral microbiome, offers novel perspectives for data mining and validation of existing data through the application of AI modelling.…”
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VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification by Muhammad Shadab Alam Hashmi, Azam Mehmood Qadri, Ali Raza, Saleem Ullah, Aseel Smerat, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani

“…This research establishes a highly effective framework for automated coffee bean classification, setting a benchmark for future studies in agricultural image analysis.…”
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Maui: modular analytics of UAS imagery for specialty crop research by Kathleen Kanaley, Maylin J. Murdock, Tian Qiu, Ertai Liu, Schuyler E. Seyram, Dominik Starzmann, Lawrence B. Smart, Kaitlin M. Gold, Yu Jiang

“…Conclusion We present a modular framework to efficiently extract spectral data for specialty crops from UAS imagery. …”
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