Development of a non-contrast CT-based radiomics nomogram for early prediction of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage by Lingxu Chen, Xiaochen Wang, Sihui Wang, Xuening Zhao, Ying Yan, Mengyuan Yuan, Shengjun Sun

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Category semantic and global relation distillation for object detection by Yanpeng LIANG, Zhonggui MA, Zongjie WANG, Zhuo LI

“…Object detection, a fundamental task in computer vision, has witnessed remarkable success in domains such as autonomous driving, robotics, and facial recognition, owing to advancements in convolutional neural networks. …”
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GDText-VM: an arbitrary-shaped scene text detector based on globally deformable VMamba by Yingnan Zhao, Zheng Hu, Fangqi Ding, Jielin Jiang, Xiaolong Xu

“…The results indicate that GDText-VM outperforms the state-of-the-art methods in terms of precision, recall, and F-measure, while maintaining efficient computation with 25.88M parameters and 40.83G FLOPs. …”
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Dual-Scale Complementary Spatial-Spectral Joint Model for Hyperspectral Image Classification by Huayue Chen, Yue Sun, Xiang Li, Bochuan Zheng, Tao Chen

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Pretreatment CT Texture Analysis for Predicting Survival Outcomes in Advanced Nonsmall Cell Lung Cancer Patients Receiving Immunotherapy: A Systematic Review and Meta‐Analysis by Yao‐Ren Zhang, Yueh‐Hsun Lu, Che‐Ming Lin, Jan‐Wen Ku

“…The included studies used diverse radiomic features for risk stratification, including texture features from gray‐level co‐occurrence matrix (GLCM) such as entropy and dissimilarity, first‐order statistical parameters including skewness and kurtosis, gray‐level run‐length matrix (GLRLM) features, and deep learning‐derived features. …”
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Wilsonian renormalization of neural network Gaussian processes by Jessica N Howard, Ro Jefferson, Anindita Maiti, Zohar Ringel

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Plantention: A general-purpose, lightweight and attention-based model for multi-crop leaf disease classification by Brindha Subburaj, Rohan M, Samhruth Ananthanarayanan, Daehan Won

“…In addition, the model has around 7.3 million parameters, making it incredibly lightweight and very ready for deployment in low-computing technology.…”
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Rough-and-Refine Model for Scene Graph Generation by Li Junliang, Lv Shirong, Li Wei

“…These features are then input alongside entity queries into the entity decoder for self-attention computation, resulting in preliminary entity representations. …”
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Sa-SNN: spiking attention neural network for image classification by Yongping Dan, Zhida Wang, Hengyi Li, Jintong Wei

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Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

“…However, these models are often complex, with numerous trainable parameters, making them resource-intensive. This work introduces the Deep Learning Model with Evolutionary Computing Approach (DLECA), a novel method for compressing and optimizing hierarchical deep learning models (HDLM). …”
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Assessing wildfire susceptibility in Iran: Leveraging machine learning for geospatial analysis of climatic and anthropogenic factors by Ehsan Masoudian, Ali Mirzaei, Hossein Bagheri

“…Utilizing advanced remote sensing, geospatial information system (GIS) processing techniques such as cloud computing, and machine learning algorithms, this research analyzed the impact of climatic parameters, topographic features, and human-related factors on wildfire susceptibility assessment and prediction in Iran. …”
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Methodology of Using CAx and Digital Twin Methods in the Development of a Multifunctional Portal Centre in Its Pre-Production Phase by Petr Bernardin, Zdenek Hajicek, Petr Janda, Josef Kozak, Frantisek Sedlacek, Vaclava Lasova, Jiri Kubicek

“…The proposed methodology was used on a specific machine, namely, a multifunctional portal centre, where features of computer-aided engineering (modelling, topology optimisation, stiffness and stress analyses, modal analyses, and analytical calculations) were combined with tools using the digital twin. …”
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Value of Pulmonary Cavity Wall Thickness Characteristics and Accompanying CT Signs in the Differential Diagnosis of Thick-wall Cancerous Cavities and Inflammatory Cavities by Zi’ao WANG, Huijie JIANG, Sheng ZHAO, Jinping LI, Zhongqi SUN, Hao LI

“…Objective: To explore the value of various computed tomography (CT) features in the differential diagnosis of pulmonary thick-wall cancerous cavitation and inflammatory cavitation. …”
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Clinical findings of acute necrotizing esophagitis complicated by diabetic ketoacidosis by Yuichiro Iwamoto, Tomohiko Kimura, Takashi Itoh, Shigehito Mori, Taku Sasaki, Mana Ohnishi, Haruka Takenouchi, Hideyuki Iwamoto, Junpei Sanada, Yoshiro Fushimi, Yukino Katakura, Fuminori Tatsumi, Masashi Shimoda, Shuhei Nakanishi, Tomoatsu Mune, Kohei Kaku, Hideaki Kaneto

“…We compared the clinical parameters and computed tomography (CT) between the groups. …”
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A lightweight model for automatic pig counting in intensive piggeries using a green inspection robot and image segmentation method by Yizhi Luo, Chen Yang, Enli Lv, Aqing Yang, Fanming Meng, Haowen Luo

“…Specifically, the C2f module is replaced with the Ghost module to reduce the model’s computational complexity. Additionally, a spatial group-enhanced attention mechanism is introduced in the neck network to enhance the model's feature fusion ability in the presence of pig occlusion and overlap. …”
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Data-driven discovery and parameter estimation of mathematical models in biological pattern formation. by Hidekazu Hishinuma, Hisako Takigawa-Imamura, Takashi Miura

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Modeling of temperature fields of details during laser hardening using the method of polyargument systems by Viktor Prokopov, Nataliia Fialko, Juliiy Sherenkovsky, Vladimir Yurchuk, Nataliia Meranova, Olha Maletskaya, Oleksandra Timoshchenko, Mark Hanzha

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Accuracy of Detecting Degrees of Lameness in Individual Dairy Cattle Within a Herd Using Single and Multiple Changes in Behavior and Gait by Xi Kang, Junjie Liang, Qian Li, Gang Liu

“…This study quantifies and analyzes key gait characteristics of cows with varying locomotion scores, evaluating their effectiveness for lameness detection in computer vision systems while considering individual specificity. …”
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A Python toolbox for neural circuit parameter inference by Alejandro Orozco Valero, Víctor Rodríguez-González, Noemi Montobbio, Miguel A. Casal, Alejandro Tlaie, Francisco Pelayo, Christian Morillas, Jesús Poza, Carlos Gómez, Pablo Martínez-Cañada

“…Abstract Computational research tools have reached a level of maturity that enables efficient simulation of neural activity across diverse scales. …”
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REDETR-RISTD: Real-Time Long-Range Infrared Small Target Detection Network Based on the Reparameterized Efficient Detection Transformer by Ning Li, Daozhi Wei

“…REDETR-RISTD maintains accuracy while significantly reducing computational complexity. First, we introduce a self-developed reparameterized multi-scale feature extraction module (RMSFE). …”
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