MSTCNet: Toward Generalization Improving for Multiframe Infrared Small Target Detection by Ruining Cui, Na Li, Junfu Liu, Huijie Zhao

“…First, we utilize the advantages of convolutional neural networks and recurrent neural networks, integrating them to build a high-performance structure. …”
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Lightweight Indoor Positioning System Based on Multiple Self-Learning Features and Key Frame Classification by C. Wang, K. Bi, B. Zhao, M. Li, Y. Chen, S. Tao, J. Yang

“…Traditional indoor positioning technologies mostly require advanced installation of hardware devices, resulting in high costs and long-term maintenance. …”
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Accurate Sugarcane Detection and Row Fitting Using SugarRow-YOLO and Clustering-Based Spline Methods for Autonomous Agricultural Operations by Guiqing Deng, Fangyue Zhou, Huan Dong, Zhihao Xu, Yanzhou Li

“…Sugarcane is mostly planted in rows, and the accurate identification of crop rows is important for the autonomous navigation of agricultural machines. …”
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Advancing Author Gender Identification in Modern Standard Arabic with Innovative Deep Learning and Textual Feature Techniques by Hanen Himdi, Khaled Shaalan

“…Although studies in Arabic have mostly concentrated on written dialects, such as tweets, there is a paucity of studies addressing Modern Standard Arabic (MSA) in journalistic genres. …”
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Design of a deep fusion model for early Parkinson’s disease prediction using handwritten image analysis by Shyamala K, Navamani T M

“…Abstract Parkinson’s Disease (PD) is a deteriorating condition that mostly affects older people. The lack of conclusive treatment for PD makes diagnosis very challenging. …”
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Determining optimal strategies for primary prevention of cardiovascular disease: a synopsis of an evidence synthesis study by Olalekan A Uthman, Lena Al-Khudairy, Chidozie Nduka, Rachel Court, Jodie Enderby, Seun Anjorin, Hema Mistry, G J Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…Cost-effectiveness analyses found most interventions had incremental cost-effectiveness ratio below £20,000–30,000 per quality-adjusted life-year. …”
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Using machine learning to predict carotid artery symptoms from CT angiography: A radiomics and deep learning approach by Elizabeth P.V. Le, Mark Y.Z. Wong, Leonardo Rundo, Jason M. Tarkin, Nicholas R. Evans, Jonathan R. Weir-McCall, Mohammed M. Chowdhury, Patrick A. Coughlin, Holly Pavey, Fulvio Zaccagna, Chris Wall, Rouchelle Sriranjan, Andrej Corovic, Yuan Huang, Elizabeth A. Warburton, Evis Sala, Michael Roberts, Carola-Bibiane Schönlieb, James H.F. Rudd

“…Explainability revealed consistent patterns in the most important radiomic features. Conclusions: Our study highlights the potential of novel image analysis techniques in extracting quantitative information beyond calcification in the identification of CAD. …”
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Diagnostic Performance of Artificial Intelligence–Based Methods for Tuberculosis Detection: Systematic Review by Seng Hansun, Ahmadreza Argha, Ivan Bakhshayeshi, Arya Wicaksana, Hamid Alinejad-Rokny, Greg J Fox, Siaw-Teng Liaw, Branko G Celler, Guy B Marks

“…ResultsRadiographic biomarkers (n=129, 84.9%) and deep learning (DL; n=122, 80.3%) approaches were predominantly used, with convolutional neural networks (CNNs) using Visual Geometry Group (VGG)-16 (n=37, 24.3%), ResNet-50 (n=33, 21.7%), and DenseNet-121 (n=19, 12.5%) architectures being the most common DL approach. …”
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Will Artificial Intelligence Replace Physicians or Augment Their Capabilities? by Sara Rahmati Roodsari, Alireza Zali, Mohammad Rahmati-Roodsari, Behina Forouzanmehr

“…In ophthalmology, convolutional and deep learning have made it possible to quickly and non-invasively interpret the retina. …”
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PatchOut: A novel patch-free approach based on a transformer-CNN hybrid framework for fine-grained land-cover classification on large-scale airborne hyperspectral images by Renjie Ji, Kun Tan, Xue Wang, Shuwei Tang, Jin Sun, Chao Niu, Chen Pan

“…Airborne hyperspectral systems can provide high-resolution hyperspectral images (HSIs) covering large scenes, enabling fine-grained land-cover classification. However, the most popular patch-based methods are limited by low computational efficiency and broken classification results, which hinders the full utilization of this powerful technology in Earth observation applications. …”
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Polarimetric SAR Ship Detection Using Context Aggregation Network Enhanced by Local and Edge Component Characteristics by Canbin Hu, Hongyun Chen, Xiaokun Sun, Fei Ma

“…In addition, neural network-based detection methods mostly rely on single polarimetric-channel scattering information and fail to fully explore the polarization properties and physical scattering laws of ships. …”
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Rough-and-Refine Model for Scene Graph Generation by Li Junliang, Lv Shirong, Li Wei

“…Existing scene graph generation methods have achieved significant success. However, most models suffer from either having too many parameters or making inaccurate judgments regarding predicates. …”
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Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses by Ying Xiong, Linpeng Yao, Jinglai Lin, Jiaxi Yao, Qi Bai, Yuan Huang, Xue Zhang, Risheng Huang, Run Wang, Kang Wang, Yu Qi, Pingyi Zhu, Haoran Wang, Li Liu, Jianjun Zhou, Jianming Guo, Feng Chen, Chenchen Dai, Shuo Wang

“…Abstract Treatment decisions for an incidental renal mass are mostly made with pathologic uncertainty. Improving the diagnosis of benign renal masses and distinguishing aggressive cancers from indolent ones is key to better treatment selection. …”
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Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis by Zohreh Javanmard, Saba Zarean Shahraki, Kosar Safari, Abbas Omidi, Sadaf Raoufi, Mahsa Rajabi, Mohammad Esmaeil Akbari, Mehrad Aria

“…Hybrid models, combining traditional and modern ML techniques, were mostly considered to predict survival rates (40.62%). …”
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Amazonian manatee critical habitat revealed by artificial intelligence‐based passive acoustic techniques by Florence Erbs, Mike van derSchaar, Miriam Marmontel, Marina Gaona, Emiliano Ramalho, Michel André

“…Manatee calls were characterized by a high emphasized frequency and high repetition rate, being mostly produced in rapid sequences. This vocal behavior strongly indicates an exchange between females and their calves. …”
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Automatic identification of clinically important Aspergillus species by artificial intelligence-based image recognition: proof-of-concept study by Chi-Ching Tsang, Chenyang Zhao, Yueh Liu, Ken P. K. Lin, James Y. M. Tang, Kar-On Cheng, Franklin W. N. Chow, Weiming Yao, Ka-Fai Chan, Sharon N. L. Poon, Kelly Y. C. Wong, Lianyi Zhou, Oscar T. N. Mak, Jeremy C. Y. Lee, Suhui Zhao, Antonio H. Y. Ngan, Alan K. L. Wu, Kitty S. C. Fung, Tak-Lun Que, Jade L. L. Teng, Dirk Schnieders, Siu-Ming Yiu, Susanna K. P. Lau, Patrick C. Y. Woo

“…While morphological examination is the most widely used for Aspergillus identification in clinical laboratories, PCR–sequencing and MALDI–TOF MS are emerging technologies in more financially-competent laboratories. …”
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Correction of crop water deficit indicators based on time-lag effects for improved farmland water status assessment by Yujin Wang, Zhitao Zhang, Yinwen Chen, Shaoshuai Fan, Haiying Chen, Xuqian Bai, Ning Yang, Zijun Tang, Long Qian, Zhengxuan Mao, Siying Zhang, Junying Chen, Youzhen Xiang

“…However, time-lag effects between canopy temperature (Tc) and environmental factors can influence their correlation with SWC, thereby complicating the identification of the most reliable diagnostic indicator. This study conducted a two-year field experiment on winter wheat under four irrigation levels (80–95 %, 65–80 %, 50–65 %, and 40–50 % field capacity). …”
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Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder by Yilu Zhao, Zhao Fu, Eric J. Barnett, Ning Wang, Kangfuxi Zhang, Xuping Gao, Xiangyu Zheng, Junbin Tian, Hui Zhang, XueTong Ding, Shaoxian Li, Shuyu Li, Qingjiu Cao, Suhua Chang, Yufeng Wang, Stephen V. Faraone, Li Yang

“…Notably, the variant that contributed most to the CNN model was NKAIN2, an ADHD-related gene, which is also associated with metabolic processes. …”
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Robust development of data-driven models for methane and hydrogen mixture solubility in brine by Kashif Saleem, Abhinav Kumar, K. D. V. Prasad, Ahmad Alkhayyat, T. Ramachandran, Protyay Dey, Navdeep Kaur, R. Sivaranjani, I. B. Sapaev, Mehrdad Mottaghi

“…In addition, it was shown that solubility is mostly affected by hydrogen mole fraction in mixture and pressure. …”
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“Locality – Adaptation” Research of Hydropower Resettlement Communities in the Jinsha River Basin: A Case Study of Ludila Hydropower Station by Fang WANG, Zhuoqi LI, Haoyi XU, Jiaqi YAN

“…ObjectiveWithin human – environment systems, river basins constitute the earliest geographical units of human activity and currently represent the most critical zones of strained human – environment interactions. …”
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