Multi-granularity Android malware fast detection based on opcode by Xuetao ZHANG, Meng SUN, Jinshuang WANG

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DamageScope: An Integrated Pipeline for Building Damage Segmentation, Geospatial Mapping, and Interactive Web-Based Visualization by Sultan Al Shafian, Chao He, Da Hu

“…This study introduces DamageScope, an integrated deep learning framework designed to detect and classify building damage levels from post-disaster satellite imagery. The proposed system leverages a convolutional neural network trained exclusively on post-event data to segment building footprints and assign them to one of four standardized damage categories: no damage, minor damage, major damage, and destroyed. …”
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SapotaNet: Paving the Way for Efficient Deep Learning with Lightweight Network Architecture by Anita Bhatt, Maulin Joshi

“…However, having a short post-harvest life and a lack of human resources result in high post-harvest losses in the case of Sapota fruit production. …”
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A fully-automated technique for cartilage morphometry in knees with severe radiographic osteoarthritis – Method development and validation by Wolfgang Wirth, Felix Eckstein

“…Objective: Denuded areas of subchondral bone (dAB) pose a challenge for fully automated segmentation of articular cartilage and subchondral bone in knees with severe radiographic osteoarthritis using convolutional neural networks (CNNs). Here we propose an automated post-processing relying on a selection-based multi-atlas registration for reconstructing the total area of subchondral bone (tAB) to overcome this issue. …”
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High sensitivity in spontaneous intracranial hemorrhage detection from emergency head CT scans using ensemble-learning approach by Juuso Takala, Heikki Peura, Riku Pirinen, Katri Väätäinen, Sergei Terjajev, Ziyuan Lin, Rahul Raj, Miikka Korja

“…A metamodel was trained on top of the four base CNNs, and simple post processing steps were applied to improve the solution’s accuracy. …”
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A Predictive Method for Unplanned Postoperative Readmission Risk Based on Heterogeneous Data by Kai YU, Xiaofeng DONG, Zhenming YUAN, Zhaojian CUI, Weibin LUO

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Time Series-Based Fault Detection and Classification in IEEE 9-Bus Transmission Lines Using Deep Learning by Somchat Jiriwibhakorn, Shazia Kanwal

“…This paper explores a time series-based deep learning technique for fault detection and classification in the IEEE 9-bus system. Post asymmetrical fault current and voltage time series data have been used to train a convolutional neural network (CNN), representing normal and faulty conditions, with convolutional and ReLU layers. …”
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Deep learning-based video analysis for automatically detecting penetration and aspiration in videofluoroscopic swallowing study by Soyoung Kwak, Jeoung Kun Kim, Jun Sung Moon, Gun Woo Lee, Sungho Kim, Min Cheol Chang

“…The model was trained with a convolutional neural network architecture, incorporating techniques to address class imbalance and optimize performance. …”
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Coseismic Landslide Mapping Based on Trans-UNet and Transfer Learning by Tianhe Ren, Wenping Gong, Jun Chen, Liang Gao, Jiahao Wu, Xuyang Xiang

“…This method provides a reliable solution for rapid post-earthquake assessment in resource-constrained environments.…”
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Multi-Pathway 3D CNN With Conditional Random Field for Automated Segmentation of Multiple Sclerosis Lesions in MRI by Reeda Saeed, Shahab U. Ansari, Muhammad Hanif, Kamran Javed, Usman Haider, Iffat Maab, Saeed Mian Qaisar, Pawel Plawiak

“…To reduce over-segmentation, we employed the CRF as a post-processing step to refine the MS lesion segmentation by minimizing false positives. …”
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Fusion of syntactic enhancement and semantic enhancement for aspect-based sentiment analysis by LIU Yao, WU Yunfei, ZHOU Hongjing, HUANG Shaonian, ZHANG Zhen

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Fusion of syntactic enhancement and semantic enhancement for aspect-based sentiment analysis by LIU Yao, WU Yunfei, ZHOU Hongjing, HUANG Shaonian, ZHANG Zhen

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Hand Gesture Recognition From Wrist-Worn Camera for Human–Machine Interaction by Hong-Quan Nguyen, Trung-Hieu Le, Trung-Kien Tran, Hoang-Nhat Tran, Thanh-Hai Tran, Thi-Lan Le, Hai Vu, Cuong Pham, Thanh Phuong Nguyen, Huu Thanh Nguyen

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High-Quality Damaged Building Instance Segmentation Based on Improved Mask Transfiner Using Post-Earthquake UAS Imagery: A Case Study of the Luding Ms 6.8 Earthquake in China by Kangsan Yu, Shumin Wang, Yitong Wang, Ziying Gu

“…Unmanned aerial systems (UASs) are increasingly playing a crucial role in earthquake emergency response and disaster assessment due to their ease of operation, mobility, and low cost. However, post-earthquake scenes are complex, with many forms of damaged buildings. …”
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Pears Internal Quality Inspection Based on X-Ray Imaging and Multi-Criteria Decision Fusion Model by Zeqing Yang, Jiahui Zhang, Zhimeng Li, Ning Hu, Zhengpan Qi

“…Pears are susceptible to internal defects during growth and post-harvest handling, compromising their quality and market value. …”
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Deep Models for Stroke Segmentation: Do Complex Architectures Always Perform Better? by Ahmed Soliman, Yalda Zafari-Ghadim, Yousif Yousif, Ahmed Ibrahim, Amr Mohamed, Essam A. Rashed, Mohamed A. Mabrok

“…Recently, several complex architectures, such as vision Transformers and attention-based convolutional neural networks (CNNs), have been introduced for this task. …”
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Leveraging LIME for Trustworthy Apple Quality Assessment by İsmail Kırbaş, Ahmet Çifci

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Daily insider threat detection with hybrid TCN transformer architecture by Xiaoyun Ye, Huangrongbin Cui, Faqin Luo, Jinlong Wang, Xiaoyun Xiong, Wencui Zhang, Jiawei Yu, Wenhao Zhao

“…This framework combines the strengths of Temporal Convolutional Networks (TCNs) and the Transformer architecture. …”
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Cimiciato defect detection in hazelnuts: CNN models applied on X-ray images by Andrea Vitale, Matteo Giaccone, Antonio Gaetano Napolitano, Flavia de Benedetta, Laura Gargiulo, Giacomo Mele

“…Insect damages affect hazelnut quality, requiring post-harvest selection based on industrial quality standards which often exceed official regulations. …”
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Improved deep learning for automatic localisation and segmentation of rectal cancer on T2‐weighted MRI by Zaixian Zhang, Junqi Han, Weina Ji, Henan Lou, Zhiming Li, Yabin Hu, Mingjia Wang, Baozhu Qi, Shunli Liu

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