A Semi-Supervised Attention Model for Identifying Authentic Sneakers by Yang Yang, Nengjun Zhu, Yifeng Wu, Jian Cao, Dechuan Zhan, Hui Xiong

“…The advancement of deep learning techniques for fine-grained object recognition creates new possibilities for genuine product identification. …”
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Predicting the exposure of mycophenolic acid in children with autoimmune diseases using a limited sampling strategy: A retrospective study by Ping Zheng, Ting Pan, Ya Gao, Juan Chen, Liren Li, Yan Chen, Dandan Fang, Xuechun Li, Fei Gao, Yilei Li

“…This study aims to use machine learning and deep learning algorithms to develop a prediction model of MPA exposure for pediatric autoimmune diseases with optimizing sampling frequency. …”
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Prospective de novo drug design with deep interactome learning by Kenneth Atz, Leandro Cotos, Clemens Isert, Maria Håkansson, Dorota Focht, Mattis Hilleke, David F. Nippa, Michael Iff, Jann Ledergerber, Carl C. G. Schiebroek, Valentina Romeo, Jan A. Hiss, Daniel Merk, Petra Schneider, Bernd Kuhn, Uwe Grether, Gisbert Schneider

“…We present a computational approach utilizing interactome-based deep learning for ligand- and structure-based generation of drug-like molecules. …”
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The Application of an Intelligent <i>Agaricus bisporus</i>-Harvesting Device Based on FES-YOLOv5s by Hao Ma, Yulong Ding, Hongwei Cui, Jiangtao Ji, Xin Jin, Tianhang Ding, Jiaoling Wang

“…This device mainly comprised a frame, camera, truss-type robotic arm, flexible manipulator, and control system. The FES-YOLOv5s deep learning target detection model was used to accurately identify and locate <i>Agaricus bisporus</i>. …”
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Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review by Aijing Luo, Wei Chen, Hongtao Zhu, Wenzhao Xie, Xi Chen, Zhenjiang Liu, Zirui Xin

“…In terms of model type, deep learning, represented by convolutional neural networks, was most frequently applied (14/23, 61%). …”
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Dual-stream disentangled model for microvascular extraction in five datasets from multiple OCTA instruments by Xiaoyang Hu, Xiaoyang Hu, Jinkui Hao, Quanyong Yi, Yitian Zhao, Jiong Zhang

“…However, noise and artifacts from different imaging instruments can interfere with segmentation, and most existing deep learning models struggle with segmenting small vessels and capturing low-dimensional structural information. …”
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Detection of Body Packs in Abdominal CT scans Through Artificial Intelligence; Developing a Machine Learning-based Model by Sayed Masoud Hosseini, Seyed Ali Mohtarami, Shahin Shadnia, Mitra Rahimi, Peyman Erfan Talab Evini, Babak Mostafazadeh, Azadeh Memarian, Elmira Heidarli

“…Conclusion: This study employed a deep learning network to identify body packs in abdominal CT scans, highlighting the importance of incorporating object shape and variability when leveraging artificial intelligence in healthcare to aid medical practitioners. …”
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Exploring the application of knowledge transfer to sports video data by Shahrokh Heidari, Gibran Zazueta, Riki Mitchell, David Arturo Soriano Valdez, Mitchell Rogers, Mitchell Rogers, Jiaxuan Wang, Ruigeng Wang, Marcel Noronha, Alfonso Gastelum Strozzi, Mengjie Zhang, Patrice Jean Delmas, Patrice Jean Delmas

“…A major limitation of training deep learning models on large datasets is the significant resource requirement for reproducing results. …”
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Early Detection of Multiwavelength Blazar Variability by Hermann Stolte, Jonas Sinapius, Iftach Sadeh, Elisa Pueschel, Matthias Weidlich, David Berge

“…For this purpose, we have developed a novel deep learning analysis framework, based on data-driven anomaly detection techniques. …”
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A Survey on Reconfigurable Intelligent Surface for Physical Layer Security of Next-Generation Wireless Communications by Ravneet Kaur, Bajrang Bansal, Sudhan Majhi, Sandesh Jain, Chongwen Huang, Chau Yuen

“…For multiple-input single-output (MISO) case, PLS strategies such as inducing artificial noise (AN), optimization algorithms, alternating optimization (AO), machine learning (ML) and deep learning (DL), and reflect matrices are discussed. …”
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A Spatiotemporal Feature Extraction Technique Using Superlet-CNN Fusion for Improved Motor Imagery Classification by Neha Sharma, Manoj Sharma, Amit Singhal, Nuzhat Fatema, Vinay Kumar Jadoun, Hasmat Malik, Asyraf Afthanorhan

“…Although there are many different methods for analyzing MI-EEG signals, research into deep learning and transfer learning approaches for MI-EEG analysis remains scarce. …”
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Predicting the tumor microenvironment composition and immunotherapy response in non-small cell lung cancer from digital histopathology images by Sushant Patkar, Alex Chen, Alina Basnet, Amber Bixby, Rahul Rajendran, Rachel Chernet, Susan Faso, Prashanth Ashok Kumar, Devashish Desai, Ola El-Zammar, Christopher Curtiss, Saverio J. Carello, Michel R. Nasr, Peter Choyke, Stephanie Harmon, Baris Turkbey, Tamara Jamaspishvili

“…Here, we introduce HistoTME, a novel weakly supervised deep learning approach to infer the tumor microenvironment (TME) composition directly from histopathology images of NSCLC patients. …”
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LipBengal: Pioneering Bengali lip-reading dataset for pronunciation mapping through lip gesturesHugging Face by Md. Tanvir Rahman Sahed, Md. Tanjil Islam Aronno, Hussain Nyeem, Md. Abdul Wahed, Tashrif Ahsan, R Rafiul Islam, Tareque Bashar Ovi, Manab Kumar Kundu, Jane Alam Sadeef

“…Captured under diverse and uncontrolled conditions, LipBengal stands as the most extensive Bengali lip-reading dataset to date, designed to facilitate robust benchmarking and validation of novel deep learning architectures. Detailed annotations extend from phoneme- level classifications to full sentence constructions, providing a granular and comprehensive dataset. …”
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SFMHANet: Surface Fitting Constrained Multidimensional Hybrid Attention Network for Aero-Optics Thermal Radiation Effect Correction by Yu Shi, ShanLin Niu, Lei Wang, Liang Ye, YaoZong Zhang, HanYu Hong

“…In order to handle multiple types of aero-optics thermal radiation effects effectively and to combine the advantages of image prior constraints and deep learning networks, we propose a surface fitting constrained multidimensional hybrid attention aero-optics thermal radiation correction network (SFMHANet) in this article. …”
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Automated on-site broiler live weight estimation through YOLO-based segmentation by Mahmoud Y. Shams, Wael M. Elmessery, Awad Ali Tayoush Oraiath, Ahmed Elbeltagi, Ali Salem, Pankaj Kumar, Tamer M. El-Messery, Tarek Abd El-Hafeez, Mohamed F. Abdelshafie, Gomaa G. Abd El-Wahhab, Ibrahim S. El-Soaly, Abdallah Elshawadfy Elwakeel

“…The study utilizes YOLO version 8, a deep learning-based network segmentation technique, for precise broiler segmentation, significantly improving weight accuracy in complex environments. …”
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An underground coal mine multi-target detection algorithm by FAN Shoujun, CHEN Xilin, WEI Liangyue, WANG Qingyu, ZHANG Shiyuan, DONG Fei, LEI Shaohua

“…Currently, underground coal mine target detection algorithms based on deep learning show poor performance in detecting complex small targets under conditions of uneven light intensity distribution, complex target environments, and imbalanced multi-class target scale distribution, often resulting in missed detection and false detection. …”
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Using partially shared radiomics features to simultaneously identify isocitrate dehydrogenase mutation status and epilepsy in glioma patients from MRI images by Yida Wang, Ankang Gao, Hongxi Yang, Jie Bai, Guohua Zhao, Huiting Zhang, Yang Song, Chenglong Wang, Yong Zhang, Jingliang Cheng, Guang Yang

“…Region of interests comprising the entire tumor and peritumoral edema were automatically segmented using a pre-trained deep learning model. Radiomic features were extracted from T1-weighted, T2-weighted, post-Gadolinium T1 weighted, and T2 fluid-attenuated inversion recovery images. …”
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Cool Neighbors: Combining Artificial Intelligence and Citizen Science to Chart the Sun’s Cosmic Neighborhood by Aaron Meisner, Dan Caselden, Austin Humphreys, Grady Robbins, Eden Schapera, J. Davy Kirkpatrick, Adam Schneider, L. Clifton Johnson, Marc Kuchner, Jacqueline Faherty, Sarah Casewell, Federico Marocco, Adam Burgasser, Daniella Bardalez Gagliuffi

“…In this case study, we describe the design and implementation of the Backyard Worlds: Cool Neighbors citizen science project, which combines image-level deep learning with Zooniverse-hosted online crowdsourcing to mine large astronomical sky maps for rare celestial objects called “brown dwarfs.” …”
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Artificial intelligence-driven identification and mechanistic exploration of synergistic anti-breast cancer compound combinations from Prunella vulgaris L.-Taraxacum mongolicum Han... by Chunlai Feng, Jiaxi Cheng, Mengqiu Sun, Chunxue Qiao, Qiuqi Feng, Naying Fang, Yingying Ge, Mengjie Rui

“…These superior extracts were subjected to liquid chromatography-mass spectrometry (LC-MS) analysis to identify their constituent compounds. A deep learning-based prediction model, DeepMDS, was applied to predict synergistic anti-breast cancer multi-compound combinations. …”
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IA na investigação, educação e prática da engenharia sísmica e estrutural - uma reflexão sobre impactos, desafios e direções futuras by Tiago Ferreira

“…Nos últimos anos, a integração de ferramentas baseadas em inteligência artificial (IA), aprendizagem automática—machine learning (ML) na terminologia anglo-saxónica—e deep-learning (DL), tem vindo a reformular os paradigmas tradicionais. …”
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