Assessing the adversarial robustness of multimodal medical AI systems: insights into vulnerabilities and modality interactions by Ekaterina Mozhegova, Asad Masood Khattak, Adil Khan, Roman Garaev, Bader Rasheed, Muhammad Shahid Anwar

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Automating field‐based floral surveys with machine learning by Nicholas Sookhan, Shane Sookhan, Devlin Grewal, J. Scott MacIvor

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Comparison of EfficientNet CNN models for multi-label chest X-ray disease diagnosis by Murat Ucan, Buket Kaya, Osman Aygun, Mehmet Kaya, Reda Alhajj

“…The analysis of chest X-ray images, which are critical for the early diagnosis of many diseases, is a difficult and time-consuming process due to the multiple labeling requirements and similar looking pathologies. …”
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Automated Distal Radius and Ulna Skeletal Maturity Grading from Hand Radiographs with an Attention Multi-Task Learning Method by Xiaowei Liu, Rulan Wang, Wenting Jiang, Zhaohua Lu, Ningning Chen, Hongfei Wang

“…<b>Methods</b>: In this study, we propose a multi-task learning framework with an attention mechanism for the joint segmentation and classification of the distal radius and ulna in hand X-ray images. …”
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Defect Prediction in CWDM Optical Modules Using Multimodal Learning by Kyu-Jeong Choi, Jia Yang, Botambu Collins, Sung-Geun Kim, Do-Jin Lim, Jin-Taek Seong

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StarNet: Indian star gooseberries dataset for quality and maturity assessment(Mendeley Data). by Pushpa B․ R․, Manohar N․, N. Shobha Rani

“…This study focuses on dataset collection, including image samples of both single and multiple-star gooseberry fruits to automate fruit grading. …”
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Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling by Maqsood Ahmed, Xiang Zhang, Yonglin Shen, Tanveer Ahmed, Shahid Ali, Ayaz Ali, Aminjon Gulakhmadov, Won-Ho Nam, Nengcheng Chen

“…However, existing research primarily focuses on single static image analysis, which does not account for the dynamic and temporal nature of air pollution. …”
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Accelerated and accurate cervical cancer diagnosis using a novel stacking ensemble method with explainable AI by Md Ismail Hossain Siddiqui, Shakil Khan, Zishad Hossain Limon, Hamdadur Rahman, Mahbub Alam Khan, Abdullah Al Sakib, S M Masfequier Rahman Swapno, Rezaul Haque, Ahmed Wasif Reza, Abhishek Appaji

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Impact of hypertension on coronary artery plaques and FFR-CT in type 2 diabetes mellitus patients: evaluation utilizing artificial intelligence processed coronary computed tomograp... by Yan Xi, Yi Xu, Zheng Shu

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AirStrum: A virtual guitar using real-time hand gesture recognition and strumming technique by Beulah ARUL, Shashank PANDA, Tushar NAIR

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Use of Vision Transformer to Classify Sea Surface Phenomena in SAR Imagery by Junfei Xia, Roland Romeiser, Wei Zhang, Tamay Ozgokmen

“…Without extensive preprocessing, the ViT model achieved approximately 80&#x0025; accuracy on HH-polarized images and 47&#x0025; on HV-polarized images, underscoring the effect of polarization differences on classification performance. …”
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Prediction of GTAW penetration state based on enhanced knowledge of dynamic morphology molten pool by Yuxiang HONG, Xiangzhi XIE, Xingxing HE, Dong DU, Baohua CHANG

“…On this basis, multi-frame molten pool contour image fusion is performed to describe the dynamic deformation of the molten pool during the welding process. …”
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Band Selection Algorithm Based on Multi-Feature and Affinity Propagation Clustering by Junbin Zhuang, Wenying Chen, Xunan Huang, Yunyi Yan

“…In this paper, we propose a band selection method (GE-AP) based on multi-feature extraction and the Affine Propagation Clustering (AP) algorithm for dimensionality reduction of hyperspectral images, aiming to improve classification accuracy and processing efficiency. …”
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Analysis of the PointNet neural network architecture by L. A. Shchenyavskaya, D. A. Gura, R. A. Dyachenko

“…Most researchers convert point cloud data into ordinary three-dimensional voxel grids or image collections, which makes the data unnecessarily voluminous and causes problems when processing them. …”
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Detection of Bacterial Leaf Spot Disease in Sesame (<i>Sesamum indicum</i> L.) Using a U-Net Autoencoder by Minju Lee, Jeseok Lee, Amit Ghimire, Yegyeong Bae, Tae-An Kang, Youngnam Yoon, In-Jung Lee, Choon-Wook Park, Byungwon Kim, Yoonha Kim

“…Hyperspectral imaging (HSI) integrates spectroscopy and imaging, providing detailed spectral–spatial information, and the selection of task-relevant wavelengths can streamline data acquisition and processing for field deployment. …”
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Visual automatic detection method for hydraulic support loss state at the working face by TENG Daiyu, NAN Bingfei

“…The average detection accuracy of the visual automatic detection method for hydraulic support loss state at the working face was 99.17%, and the single frame image processing time is 36 ms, meeting the real-time and reliability requirements for detecting support loss states in coal mining face AI video monitoring systems.…”
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A Dual-Sequence MRI-Based Radiomics Model for Predicting High-Intensity Focused Ultrasound Ablation Efficacy in Adenomyosis Treatment by Sun M, Deng X, Xing H, Zhang R, Fu B, Ai T, Wang F, Wang X, Chen L, Mao X, Wu F

“…This process included feature extraction, selection, model construction, and evaluation. …”
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Combining Convolutional Neural Network (CNN) and Grad-CAM for Parkinson’s Disease Prediction and Visual Explanation by Reyhaneh Dehghan, Marjan Naderan, Seyed Enayatallah Alavi

“…In this study, a Convolutional Neural Network (CNN) namely ConvNet, is used to discriminate Parkinson's patients based on Single Photon Emission Computed Tomography (SPECT) images acquired from the PPMI database. …”
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Retina‐Inspired X‐Ray Optoelectronic Synapse Using Amorphous Ga2O3 Thin Film by Huili Liang, Xiaoyan Tang, Hang Shao, Rui Zhu, Shizhi Deng, Xiaozhi Zhan, Tao Zhu, Jiwei Wang, Jihua Zhang, Guangyu Zhang, Zengxia Mei

“…The image contrast can be apparently improved under a series of X‐ray pulses due to an outstanding long‐term plasticity of the single pixel, which is beneficial to the subsequent image recognition and classification based on artificial neural network. …”
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Enhancing medical explainability in deep learning for age-related macular degeneration diagnosis by Lily Shi

“…Experimental results demonstrate robust performance, achieving an area under the curve (AUC) of 0.96 for classification and a Dice similarity coefficient (DSC) of 0.59 for segmentation, outperforming single-task models. …”
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