YOLOv11-ND: A Method for Identifying Traffic Targets in Nighttime Urban Environments by Danyang Zhu, Hao Zhou, Yunlong Gao, Yongjuan Wang

“…Lastly, the model is optimized using the Focaler-GIoU loss function to further enhance the detection performance. …”
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SWRD–YOLO: A Lightweight Instance Segmentation Model for Estimating Rice Lodging Degree in UAV Remote Sensing Images with Real-Time Edge Deployment by Chunyou Guo, Feng Tan

“…The model employs an optimized loss function to improve localization accuracy, achieving precise lodging area segmentation. …”
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Auto-Probabilistic Mining Method for Siamese Neural Network Training by Arseniy Mokin, Alexander Sheshkus, Vladimir L. Arlazarov

“…However, it has its own shortcomings due to the known imperfections of widely used loss functions such as contrastive loss and triplet loss, as well as sample mining methods. …”
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LS-YOLO: A Lightweight, Real-Time YOLO-Based Target Detection Algorithm for Autonomous Driving Under Adverse Environmental Conditions by Cheng Ju, Yuxin Chang, Yuansha Xie, Dina Li

“…The LS-YOLO incorporates a MACA module to capture both global and local features, an SPDD module to reduce computational complexity, and a DR-Concat module to optimize feature fusion. Additionally, an improved ATFL-Wasserstein loss function is employed to enhance the learning capability for small objects and hard samples. …”
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Insulator Defect Detection Algorithm Based on Improved YOLOv11n by Junmei Zhao, Shangxiao Miao, Rui Kang, Longkun Cao, Liping Zhang, Yifeng Ren

“…Key innovations include a redesigned C3k2 module that incorporates multidimensional dynamic convolutions (ODConv) for improved feature extraction, the introduction of Slimneck to reduce model complexity and computational cost, and the application of the WIoU loss function to optimize anchor box handling and to accelerate convergence. …”
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Neural Network-Based Analysis of Forest Fire Aftermath in Class-Imbalanced Remote Sensing Earth Image Classification by V. Hnatushenko, V. Hnatushenko, V. Hnatushenko, D. Soldatenko

“…In this paper, we proposed convolution neural networks for semantic segmentation, where sample imbalance is considered based on a particular loss function coupled with data augmentation. To illustrate our method, we use Sentinel-2 remote sensing (RS) images covering a number of regions in Ukraine, and then we create an image dataset of the region and for training and testing make data augmentation. …”
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Self-supervised denoising method for single neutron image based on the S2S-NR network by Wangtao Yu, Peng Xu, Xinghui Cai, Man Zhou, Jie Bao

“…Furthermore, we incorporate no-reference image quality assessment metrics into the loss function to optimize the training process. Experimental results show that the method achieves state-of-the-art denoising performance on both simulated and real fast neutron images, demonstrating the effectiveness and practicality of this method as a potential solution for the denoising task in fast neutron imaging.…”
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Brain CT image classification based on mask RCNN and attention mechanism by Shoulin Yin, Hang Li, Lin Teng, Asif Ali Laghari, Ahmad Almadhor, Michal Gregus, Gabriel Avelino Sampedro

“…The deformable convolution is embedded to the two modules to extract global features. Finally, the loss function is improved to further optimize the precision of target edge segmentation in the Mask RCNN branch. …”
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Reconstruction of the Proximal Portion of the Brachial Triceps Muscle with Homologous Graft: A Case Report by Eduardo Borges Ferreira Jr, Daniel Yiteh Lin, Maria Mascarenhas, Beatriz Lassance, Luciana Andrade da Silva, Alberto Naoki Miyazaki

“…Conclusion: The case report demonstrates that reconstruction of the proximal portion of the BT muscle with a homologous graft is a promising approach for treating this type of injury, bringing significant improvements in muscle function and esthetics. Furthermore, a multidisciplinary approach, postoperative surveillance, and the continuous pursuit of technical advancements are essential to optimize results and minimize complications, broadening therapeutic options in complex cases.…”
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Visual related quality of life after ICL V4c implantation in high myopia patients: a mini review by Huailan Zhao, Siquan Zhu

“…High myopia (≥ − 6.00 D) poses significant challenges to visual function and quality of life, with implantable collamer lens (ICL) V4c implantation emerging as a pivotal treatment. …”
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Enhancing memory retrieval in generative agents through LLM-trained cross attention networks by Chuanyang Hong, Qingyun He

“…In a novel approach, we incorporated LLM assistance, comparing memories retrieved by our model with those extracted using a base method during training, and constructing a novel loss function based on these comparisons to optimize the training process effectively. …”
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LCDDN-YOLO: Lightweight Cotton Disease Detection in Natural Environment, Based on Improved YOLOv8 by Haoran Feng, Xiqu Chen, Zhaoyan Duan

“…Additionally, the CBAM attention mechanism is incorporated into the neck network to improve model performance. A Focal-EIoU loss function is also integrated to optimize the model’s training process. …”
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Enhancing Binary Convolutional Neural Networks for Hyperspectral Image Classification by Xuebin Tang, Ke Zhang, Xiaolei Zhou, Lingbin Zeng, Shan Huang

“…Additionally, to address suboptimal training issues, EBCNN employs a dynamic curriculum learning strategy underpinned by a confidence-aware loss function, Superloss, enabling progressive binarization and enhancing its classification effectiveness. …”
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Enhancing HVAC Control Systems Using a Steady Soft Actor–Critic Deep Reinforcement Learning Approach by Hongtao Sun, Yushuang Hu, Jinlu Luo, Qiongyu Guo, Jianzhe Zhao

“…Specifically, we introduce cumulative returns into the SAC framework and recalculate target values, which reduces the loss function. The proposed HVAC control algorithm achieved 24.2% energy savings compared to the baseline SAC algorithm. …”
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Nitrate-Nitrogen Leaching and Modeling in Intensive Agriculture Farmland in China by Ligang Xu, Hailin Niu, Jin Xu, Xiaolong Wang

“…It can also be concluded that the model after calibration is a useful tool to optimize as a function of the combination “climate-crop-soil-bottom boundary condition” the nitrogen application strategy resulting for the environment in an acceptable level of nitrate leaching. …”
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Minimum Cost Flow Problems in Generalized Fuzzy environments. Credibilistic CVaR minimization approach by Hande Günay Akdemir, Nurdan Kara, Hale Gonce Kocken

“…The uncertainty is eliminated using the total cost as a loss function and credibilistic conditional value at risk (CVaR) minimization. …”
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Infrastructure-based sensor fusion for acquiring gross vehicle weight rating classifications by Guoliang Feng, Yiqiao Li, Andre Y.C. Tok, Stephen G. Ritchie

“…Next, signature-based and image-based classification models were developed for GVWR classification, with model designed to function independently. The signature-based GVWR classification model was trained with a multi-layer perceptron (MLP) architecture and optimized through the implementation of a weighted cross-entropy loss function. …”
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Mathematical model for prediction of Tuberculosis in Nigeria using hybrid fractional differential equations and artificial neural network methods by Samson Linus Manu, Shikaa Samuel, Taparki Richard, Eshi Priebe Dovi

“…These FODEs were discretized, and the parameter values were numerically estimated using the Grünwald-Letnikov method while the Hybrid FODE-ANN framework features a NN architecture with one input layer, 15 hidden layers of 100 neurons each, and a hyperbolic tangent (tanh) activation function. Training of the NN involves minimizing a loss function combining data fit and system constraints, optimized using the Adam and L-BFGS algorithms, achieving a high degree of accuracy with an MSE of 6.005×10−6. …”
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Isolation and Characterization of Laccase from <i>Trichoderma asperellum</i> Tasjk65 by Kehe Fu, Lili Fan, Qi Li, Jiaming Ji, Zhenying Huang, Ting Huang

“…In this study, a high-laccase-producing <i>Trichoderma</i> strain was isolated from soil, and the conditions for laccase production were optimized. Additionally, the laccase-related gene was cloned, and its function was analyzed. …”
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Improved YOLO for long range detection of small drones by Sicheng Zhou, Lei Yang, Huiting Liu, Chongqin Zhou, Jiacheng Liu, Yang Wang, Shuai Zhao, Keyi Wang

“…The neck structure is enhanced with a collaborative attention mechanism and multi-scale fusion, improving feature representation. An optimized loss function refines bounding box matching for small targets, while a pruning strategy removes redundant filters, boosting computational efficiency. …”
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