RTDETR-MARD: A Multi-Scale Adaptive Real-Time Framework for Floating Waste Detection in Aquatic Environments by Baoshan Sun, Haolin Tang, Liqing Gao, Kaiyu Bi, Jiabao Wen

“…Third, we implement the Wise-IoU loss function to optimize localization accuracy through high-quality anchor supervision. …”
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The Value of Alarm Features in Identifying Organic Causes of Dyspepsia by Lone Galmstrup Madsen, Peter Bytzer

“…Alarm features such as age, significant weight loss, use of nonsteroidal anti-inflammatory drugs, signs of bleeding and dysphagia may help stratify dyspeptic patients and help optimize the use of endoscopy resources.…”
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Unsupervised spatio-temporal state estimation for fine-grained anomaly diagnosis of cyber-physical systems by SUN Haili, HUANG Yan, HAN Lansheng, ZHOU Chunjie

“…Afterwards, three associated alignment loss functions and a reconstruction loss were constructed to jointly optimize the model. …”
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Strategic Wholesale Pricing for an Incumbent Supplier Facing with a Competitive Counterpart by Jianwu Sun

“…We propose a profit function which considers both the present loss and future loss from a wholesale price and then study the optimal wholesale prices for different objectives about this profit function for the incumbent supplier. …”
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Role of sphingolipid metabolism signaling in a novel mouse model of renal osteodystrophy based on transcriptomic approach by Yujia Wang, Yan Di, Yongqi Li, Jing Lu, Bofan Ji, Yuxia Zhang, Zhiqing Chen, Sijie Chen, Bicheng Liu, Rining Tang, Yuanyuan Ji

“…To address this gap, we established a stable mouse model of ROD using an optimized adenine-enriched diet and conducted exploratory analyses through ribonucleic acid sequencing (RNA-seq). …”
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New design paradigm for federated edge learning towards 6G:task-oriented resource management strategies by Zhiqin WANG, Jiamo JIANG, Peixi LIU, Xiaowen CAO, Yang LI, Kaifeng HAN, Ying DU, Guangxu ZHU

“…According to the relationship between the optimal value interval of the loss function and the training time, the optimal quantization series and the optimal bandwidth allocation strategy are obtained by solving the training time minimization problem. 2. …”
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Enhanced Conformer-Based Speech Recognition via Model Fusion and Adaptive Decoding with Dynamic Rescoring by Junhao Geng, Dongyao Jia, Zihao He, Nengkai Wu, Ziqi Li

“…Additionally, to further optimize the decoding process, we introduce a penalty function mechanism as a regularization technique to reduce the model’s dependence on a single decoding approach. …”
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Physical exercise for primary sarcopenia: an expert opinion by Antimo Moretti, Federica Tomaino, Marco Paoletta, Sara Liguori, Sara Liguori, Silvia Migliaccio, Mariangela Rondanelli, Angelo Di Iorio, Raffaello Pellegrino, Davide Donnarumma, Daniele Di Nunzio, Giuseppe Toro, Francesca Gimigliano, Maria Luisa Brandi, Giovanni Iolascon

“…Sarcopenia is the age-related loss of skeletal muscle mass and function. Recently, research has focused on defining diagnostic criteria for this condition, now recognized as a muscle disease with a specific identifying code (ICD-10: M62.84). …”
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Fusion of RetinaFace and improved FaceNet for individual cow identification in natural scenes by Lingling Yang, Xingshi Xu, Jizheng Zhao, Huaibo Song

“…FaceNet's core feature network was enhanced through MobileNet integration, and the loss function was jointly optimized with Cross Entropy Loss and Triplet Loss to achieve a quicker and more stable convergence curve. …”
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Downstream Semantic Segmentation Model for Low-Level Surface Crack Detection by Thitirat Siriborvornratanakul

“…An off-the-shelf semantic segmentation model named DeepLabV3-ResNet101 is used as a base model and then experimented with different loss functions and training strategies. Our experimental results have revealed that the downstream models trained by the classic cross-entropy loss function cannot provide reasonable results in pixel-level crack detection. …”
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Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…Aerial devices with limited communication and computation resource can offload partial nonprivacy data samples to proximity D2D pair, which can assist to train FL models. An optimization problem is proposed to minimize the total energy consumption and the loss function of local FL models. …”
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Learning Energy-Efficient Transmitter Configurations for Massive MIMO Beamforming by Hamed Hojatian, Zoubeir Mlika, Jeremy Nadal, Jean-Francois Frigon, Francois Leduc-Primeau

“…Finally, towards obtaining a system that can be trained using in-the-field measurements, we investigate the ability of the model to be trained exclusively using imperfect channel state information (CSI), both for the input to the deep learning model and for the calculation of the loss function. Simulation results show that the proposed solutions can outperform conventional methods in terms of EE while being trained with imperfect CSI. …”
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An advanced deep learning method for pepper diseases and pests detection by Xuewei Wang, Jun Liu, Qian Chen

“…Built upon YOLOv10n, YOLO-Pepper incorporates four major innovations: (1) an Adaptive Multi-Scale Feature Extraction (AMSFE) module that improves feature capture through multi-branch convolutions; (2) a Dynamic Feature Pyramid Network (DFPN) enabling context-aware feature fusion; (3) a specialized Small Detection Head (SDH) tailored for minute targets; and (4) an Inner-CIoU loss function that enhances localization accuracy by 18% compared to standard CIoU. …”
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A hybrid LSTM-transformer model for accurate by Tianren Zhao, Yanhui Zhang, Minghao Wang, Wei Feng, Shengxian Cao, Gong Wang

“…The regression task is optimized using the Mean Squared Error loss function and trained with the Adam optimizer. …”
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Convergence Analysis of the Approximation Problems for Solving Stochastic Vector Variational Inequality Problems by Meiju Luo, Kun Zhang

“…For solving this problem, we employ the regularized gap function of SVVIP to the loss function and then give a low-risk conditional value-at-risk (CVaR) model. …”
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PHRF-RTDETR: a lightweight weed detection method for upland rice based on RT-DETR by Xianjin Jin, Jinheng Zhang, Fei Wang, Mengyan Zhao, Yunshuang Wang, Jianping Yang, Jinfeng Wu, Bing Zhou

“…Finally, the conventional GIoU loss is replaced with the Focaler-WIoUv3 loss function to significantly improve the model’s generalization performance.ResultsThe experimental results show that PHRF-RTDETR achieves precision, recall, mAP50, and mAP50:95 scores of 92%, 85.6%, 88.2%, and 76.6%, respectively, with all metrics deviating by less than 1.7 percentage points from the baseline model in upland rice weed detection. …”
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Real time wire rope detection method based on Rockchip RK3588 by Mengpeng Qian, Yong Wang, Shaoqing Liu, Zhanghou Xu, Zhenshan Ji, Ming Chen, Hailong Wu, Zuchao Zhang

“…To enhance non-destructive wire rope inspection, a Mini-YOLO model was developed by integrating MobileNetV3, the Coordinate Attention (CA) mechanism, and a novel loss function, Inner-IoU, into the YOLOv8 framework. …”
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Application of Generative Adversarial Networks Based on Global and Local Feature Information in Hippocampus Segmentation by WEI Zhihong, KONG Xudong, KONG Yan, YAN Shiju, DING Yang, WEI Xianding, KONG Dong, YANG Bo

“…First, to improve network stability and segmentation accuracy while reducing the likelihood of problems such as information loss and gradient explosion, we proposed the global GAN (GGAN) by optimizing the generator and loss function of GAN. …”
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Dual Focus-3D: A Hybrid Deep Learning Approach for Robust 3D Gaze Estimation by Abderrahmen Bendimered, Rabah Iguernaissi, Mohamad Motasem Nawaf, Rim Cherif, Séverine Dubuisson, Djamal Merad

“…Key innovations include a multimodal feature fusion strategy, an angular loss function optimized for 3D gaze prediction, and regularization techniques to mitigate overfitting. …”
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YOLOv9-GDV: A Power Pylon Detection Model for Remote Sensing Images by Ke Zhang, Ningxuan Zhang, Chaojun Shi, Qiaochu Lu, Xian Zheng, Yujie Cao, Xiaoyun Zhang, Jiyuan Yang

“…Finally, the Variable Minimum Point Distance Intersection over Union (VMPDIoU) loss is proposed to optimize the model’s loss function. …”
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