In-context learning enables multimodal large language models to classify cancer pathology images by Dyke Ferber, Georg Wölflein, Isabella C. Wiest, Marta Ligero, Srividhya Sainath, Narmin Ghaffari Laleh, Omar S. M. El Nahhas, Gustav Müller-Franzes, Dirk Jäger, Daniel Truhn, Jakob Nikolas Kather

“…Abstract Medical image classification requires labeled, task-specific datasets which are used to train deep learning networks de novo, or to fine-tune foundation models. …”
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Early monitoring of drought stress in safflower (Carthamus tinctorius L.) using hyperspectral imaging: A comparison of machine learning tools and feature selection approaches by Fatemeh Salek, Seyed Ahmad Mireei, Abbas Hemmat, Mehrnoosh Jafari, Mohammad R. Sabzalian, Majid Nazeri, Wouter Saeys

“…Classification analysis was performed using the full mean spectral data with partial least squares discriminant analysis, soft independent modeling of class analogy (SIMCA), support vector machines, and artificial neural network (ANN) classifiers. …”
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Multi-label classification with deep learning techniques applied to the B-Scan images of GPR by El Karakhi, Soukayna, Reineix, Alain, Guiffaut, Christophe

“…In this study, a multi-label classification (MLC) model based on transfer learning and data augmentation has been developed to generate multiple information elements on the same image and to realize classification. …”
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Visualization analysis of CBL application in Chinese and international medical education based on big data mining by Junyan Yue, Yun Shang, Hongkai Cui, Changhua Liang, Qingwu Wu, Junqiang Zhao, Huifang Wang, Dongmin Han, Zhiping Zhu

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Comparative Analysis of Multi-Resolution Remote Sensing Data for Accurate Road Segmentation in Urban Environments by M. R. Çevikalp, B. Mutlu, M. Yanalak, N. Musaoğlu

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Multi-source Data-driven Analysis of Deformation and Influencing Factors for Expansive Soil Canal Slopes by ZHANG Yuhan, HU Jiang, LI Xing

“…This approach facilitates a comprehensive analysis of deformation patterns at the slope surface and various subsurface depths, while elucidating the dominant controlling factors governing expansive soil canal slope behavior.Results and Discussions　The study focused on a deep excavated expansive soil canal section (Stake 8+886~12+921) of a major water diversion project, yielding the following key findings: 1) The analysis of 128 Sentinel-1A images from March 2017 to December 2021 revealed that the deformation data obtained through SBAS-InSAR method showed less than 3mm discrepancy with surface vertical displacement measurements at monitoring points (fourth-stage berm at 9+363 and third-stage berm at 11+400), with consistent deformation trends, confirming the reliability of SBAS-InSAR for canal slope deformation monitoring. 2) The study section exhibited LOS deformation rates ranging from -10 to 24 mm/a, demonstrating overall uplift characteristics, with positive LOS deformation showing annual increase. …”
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Learning Power Systems Waveform Incipient Patterns Through Few-Shot Meta-Learning by Lixian Shi, Qiushi Cui, Yang Weng, Yigong Zhang, Shilong Chen, Jian Li, Wenyuan Li

“…However, traditional detection methods cannot achieve satisfactory performance when faced with limited data. Besides, some signal analysis methods based on waveform conversion to images cannot obtain understandable image data and cannot analyze both current and voltage signals simultaneously. …”
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Cross‐Domain Foundation Model Adaptation: Pioneering Computer Vision Models for Geophysical Data Analysis by Zhixiang Guo, Xinming Wu, Luming Liang, Hanlin Sheng, Nuo Chen, Zhengfa Bi

“…FMs, which are large neural networks trained on massive data sets, excel in diverse tasks with remarkable adaptability and generality. …”
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Extracting the Epoch of Reionization Signal with 3D U-Net Neural Networks Using a Data-driven Systematic Effect Model by Li-Yang Gao, Léon V. E. Koopmans, Florent G. Mertens, Satyapan Munshi, Yichao Li, Stefanie A. Brackenhoff, Emilio Ceccotti, J. Kariuki Chege, Anshuman Acharya, Raghunath Ghara, Sambit K. Giri, Ilian T. Iliev, Garrelt Mellema, Xin Zhang

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Shinyscreen: mass spectrometry data inspection and quality checking utility by Todor Kondić, Anjana Elapavalore, Jessy Krier, Adelene Lai, Hiba Mohammed Taha, Mira Narayanan, Emma L. Schymanski

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A dual GAN with identity blocks and pancreas-inspired loss for renewable energy optimization by Mostafa Elbaz, Wael Said, Gamal M. Mahmoud, Hanaa Salem Marie

“…Our comparative analysis revealed that Penca-GAN consistently achieved the lowest Fréchet Inception Distance (FID) scores (164.45 for SKY, 113.54 for Solar, and 109.34 for Wind Turbine), indicating superior image quality compared to other architectures. …”
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Towards precision diagnosis: a novel hybrid DC-CAD model for lung disease detection leveraging multi-scale capsule networks and temporal dynamics by Esther Stacy E. B. Aggrey, Qin Zhen, Seth Larweh Kodjiku, Linda Delali Fiasam, Collins Sey, Chiagoziem C. Ukwuoma, Evans Aidoo, Emmanuel Osei-Mensah

“…However, traditional diagnostic approaches and standard deep learning models often face challenges in effectively analyzing the complex spatial and temporal variations in medical imaging data, particularly in CT scans. To address these challenges, we propose DC-CAD, a novel hybrid framework that integrates Dilated Capsule Networks, Channel-wise Attention Mechanisms, and Distanced Long Short-Term Memory for precise and early diagnosis of lung diseases. …”
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RIS-UNet: A Multi-Level Hierarchical Framework for Liver Tumor Segmentation in CT Images by Yuchai Wan, Lili Zhang, Murong Wang

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Super-Resolution of Landsat-8 Land Surface Temperature Using Kolmogorov–Arnold Networks with PlanetScope Imagery and UAV Thermal Data by Mahdiyeh Fathi, Hossein Arefi, Reza Shah-Hosseini, Armin Moghimi

“…To address these challenges, this study presents a novel approach to generate LST_SR maps by integrating Low-Resolution Landsat-8 LST (LST_LR) with High-Resolution PlanetScope images (I_HR) and UAV-derived thermal imagery (T_HR) using the Kolmogorov–Arnold Network (KAN) model. …”
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Dual-stage segmentation and classification framework for skin lesion analysis using deep neural network by Khadija Manzoor, Nauman U Gilal, Marco Agus, Jens Schneider

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YOLOv8 framework for COVID-19 and pneumonia detection using synthetic image augmentation by Uddin A Hasib, Raihan Md Abu, Jing Yang, Uzair Aslam Bhatti, Chin Soon Ku, Lip Yee Por

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Prediction of Time-evolving Radial Magnetic Fields on the Solar Surface Using Deep Learning by Hyun-Jin Jeong, Stefaan Poedts, Haopeng Wang, Ekatarina Dineva, Panagiotis Gonidakis, Francesco Carella, George Miloshevich, Luis Linan, Harim Lee

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Contrastive Learning with Image Deformation and Refined NT-Xent Loss for Urban Morphology Discovery by Chunliang Hua, Daijun Chen, Mengyuan Niu, Lizhong Gao, Junyan Yang, Qiao Wang

“…Representative urban types were identified, particularly some types located at the urban fringe. The data analysis demonstrated the effectiveness of our image deformation pipeline and loss function, and the sociological analysis illustrated the unique urban functions of these urban types.…”
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Liver Tumor Prediction using Attention-Guided Convolutional Neural Networks and Genomic Feature Analysis by S. Edwin Raja, J. Sutha, P. Elamparithi, K. Jaya Deepthi, S.D. Lalitha

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Two forecasting model selection methods based on time series image feature augmentation by Wentao Jiang, Quan Wang, Hongbo Li

“…Abstract Forecasting and early warning of agricultural product prices is a crucial task in stream data event analysis and agricultural data mining. …”
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