Comparative analysis of attentional mechanisms in rice pest identification by Yongjun Xiao, Xiangruo Zhang, Ziao Chen, Jingxuan Tan, Linyu Zhou, Chunxian Jiang, Lijia Xu, Zhiyong Li

“…Experimental results show that Bionic Attention improves detection performance by indirectly enhancing the loss function, allowing the model to acquire more fine-grained information during the feature extraction stage, thereby improving detection accuracy.…”
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YOLO-BOS: An Emerging Approach for Vehicle Detection with a Novel BRSA Mechanism by Liang Zhao, Lulu Fu, Xin Jia, Beibei Cui, Xianchao Zhu, Junwei Jin

“…Lastly, we introduce Shape-IOU, a new loss function that significantly enhances the accuracy and robustness of detection results for vehicles of varying sizes. …”
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Classification of OCT Images of the Human Eye Using Mobile Devices by Agnieszka Stankiewicz, Tomasz Marciniak, Nina Budna, Róża Chwałek, Marcin Dziedzic

“…With the application, classification can be performed on an image chosen from the user’s files or an image acquired using the photo-taking function. The results of the classification are displayed for three neural networks, along with the respective classification times for each neural network and the associated image undergoing the classification task. …”
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MSO‐DETR: Metric space optimization for few‐shot object detection by Haifeng Sima, Manyang Wang, Lanlan Liu, Yudong Zhang, Junding Sun

“…Meanwhile, a novel similarity measure function based on Poincaré distance is proposed to evaluate the distance of various types of objects in the feature space. …”
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Time Series Anomaly Detection Using Transformer-Based GAN With Two-Step Masking by Ah-Hyung Shin, Seong Tae Kim, Gyeong-Moon Park

“…Time series anomaly detection is a task that determines whether an unseen signal is normal or abnormal, and it is a crucial function in various real-world applications. …”
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A Bivariate Model for Correlated and Mixed Outcomes: A Case Study on the Simultaneous Prediction of Credit Risk and Profitability of Peer-to-Peer (P2P) Loans by Yan Wang, Xuelei Sherry Ni, Huan Ni, Sanad Biswas

“…Then to solve the multi-target problem, we design a novel loss function based on the assumption that the discrete outcome follows a Bernoulli distribution, and the continuous outcome is normally distributed conditional on the discrete output. …”
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A Simple and Effective KAN-Based Architecture for Accurate Battery RUL Prediction by Guangzai Ye, Li Feng, Jianlan Guo, Yuqiang Chen, Shufei Li

“…It also incorporates a channel-independent KANs structure with a regularized weighted loss function to handle variable-specific degradation patterns. …”
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A YOLOv8n-T and ByteTrack-Based Dual-Area Tracking and Counting Method for Cucumber Flowers by Liyang Su, Shujuan Zhang, Hongtu Zhang, Xiangsen Meng, Xiongkui He

“…The YOLOv8n-T incorporates a Coordinate Attention (CA) mechanism and lightweight modules while optimizing the loss function, thereby improving floral feature extraction capabilities and reducing computational complexity. …”
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Kinetic Responses to Acute Blood Flow Restriction Exposure in Young Physically Active Women During Isometric Mid-Thigh Pull by Sebastián Aliste-Flores, Luis Javier Chirosa-Ríos, Ignacio Chirosa-Ríos, Daniel Jerez-Mayorga

“…These findings indicate that acute BFR application, even when volitional fatigue is induced, does not substantially impair neuromuscular function in isometric settings. These findings indicate that acute exposure to BFR, even under fatiguing conditions, does not substantially impair isometric force production or explosive performance in young physically active women. …”
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An Edge-Aware Multitask Network Based on CNN and Transformer Backbone for Farmland Instance Segmentation by Yang Liu, Tong Zhang, Yanru Huang, Furong Shi

“…To reduce the pseudoedges, we design an edge loss function that is relatively sensitive to pseudoedges. …”
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The effect of transcranial alternating current stimulation over the supplementary motor area on bimanual coordination in elderly people by Asiyeh Dehghani, Hamid Reza Taheri Torbati, Mehdi Sohrabi, Afkham Daneshfar, Mohammad Saber Sotoodeh

“…Background: Transcranial alternating current stimulation (tACS) is a non-invasive method that offers a potential solution to reduce the effects of aging on brain function.Aim: The aim of this study was to investigate the effect of offline tACS over the supplementary motor area on bimanual coordination in elderly people.Materials and Methods: Thirty-one women aged of 60-75 years were selected as convenience. …”
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A decomposition approach for integrated locomotive scheduling and driver assignment in rail freight transport by Andreas Bärmann, Alexander Martin, Jonasz Staszek

“…The objective function of this model makes sure that as many trains as possible are running. …”
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Cross-Subject EEG-Based Emotion Recognition Using Deep Metric Learning and Adversarial Training by Hawraa Razzaq Abed Alameer, Pedram Salehpour, Seyyed Hadi Aghdasi, Mohammad-Reza Feizi-Derakhshi

“…To address these issues, this paper presents a novel deep similarity learning loss specific to the emotion recognition task. This loss function minimizes intra-emotion class variations of EEG segments with different subject labels while maximizing inter-emotion class variations. …”
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Respiratory phenotypes of neuromuscular diseases: A challenging issue for pediatricians by Melissa Borrelli, Gaetano Terrone, Roberto Evangelisti, Flora Fedele, Adele Corcione, Francesca Santamaria

“…Restriction of breathing, impaired gas exchange, decline of lung function and sleep disordered breathing progressively develop because of muscular weakness and culminate in respiratory failure. …”
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A compositional model for effort‐aware Just‐In‐Time defect prediction on android apps by Kunsong Zhao, Zhou Xu, Meng Yan, Lei Xue, Wei Li, Gemma Catolino

“…In this study, a novel compositional model, called KPIDL, is proposed to conduct the JIT defect prediction task for Android apps. More specifically, KPIDL first exploits a feature learning technique to preprocess original data for obtaining better feature representation, and then introduces a state‐of‐the‐art cost‐sensitive cross‐entropy loss function into the deep neural network to alleviate the class imbalance issue by considering the prior probability of the two types of classes. …”
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Balance rehabilitation and Long Covid syndrome: effectiveness of thermal water treatment vs. home-based program by Maria Chiara Maccarone, Paola Contessa, Edoardo Passarotto, Gianluca Regazzo, Stefano Masiero, Stefano Masiero

“…On the other hand, at the 3-month follow-up, individuals who enrolled in the spa-resort program exhibited improvements in the standard deviation of oscillations in the antero-posterior direction, indicating ongoing benefits over time.DiscussionThese findings suggest that appropriate rehabilitation programs, whether at home or in spa resorts, can contribute to enhancing overall physical function in these patients.…”
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Computational modelling and neural correlates of reinforcement learning following three-week escitalopram: a double-blind, placebo-controlled semi-randomised study by Christelle Langley, Graham K. Murray, Sophia Armand, Franziska Knolle, Rudolf N. Cardinal, Annette Johansen, Peter S. Jensen, Jianfeng Feng, Dea S. Stenbæk, Gitte M. Knudsen, Patrick M. Fisher, Barbara J. Sahakian

“…Consequently, we aimed to investigate the effect of a three-week administration of the SSRI, escitalopram, on a reinforcement learning paradigm during functional magnetic resonance imaging. The study used a double-blind, placebo-controlled design with 64 healthy volunteers. …”
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HSD²Former: Hybrid-Scale Dual-Domain Transformer with Crisscrossed Interaction for Hyperspectral Image Classification by Binxin Luo, Meihui Li, Yuxing Wei, Haorui Zuo, Jianlin Zhang, Dongxu Liu

“…HSD²Former consists of three functional modules: dual-dimension multiscale convolutional embedding (D²MSCE), mixed domainFormer (MDFormer), and pyramid scale fusion block (PSFB). …”
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Diminished reward circuit response underlies pain avoidance learning deficits in problem drinkers by Thang M. Le, Takeyuki Oba, Chiang-Shan R. Li

“…Nevertheless, how reward circuit dysfunctions impact avoidance learning and contribute to drinking behavior remains poorly understood. Here, we combined functional imaging and a probabilistic learning go/nogo task to examine the neural processes underlying proactive pain avoidance learning in 103 adult drinkers. …”
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Predicting imitative performance through cortico-cerebellar circuits: A multivariate and effective connectivity study by Antonino Errante, Giuseppe Ciullo, Settimio Ziccarelli, Alessandro Piras, Cristina Russo, Leonardo Fogassi

“…The present study aimed at investigating whether functional interaction between cortical areas and the cerebellum during the observation of complex bimanual actions can predict individual ability to imitate the same actions. …”
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