Semantic-Aware Low-Light Image Enhancement by Learning from Multiple Color Spaces by Bo Jiang, Xuefei Wang, Naidi Yang, Yuhan Liu, Xi Chen, Qiwen Wu

“…Inspired by human visual perception mechanisms, our enhanced loss function calculates color discrepancies across three color spaces—RGB, LAB, and LCH—through three components: <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>l</mi><mi>o</mi><mi>s</mi><msub><mi>s</mi><mrow><mi>r</mi><mi>g</mi><mi>b</mi></mrow></msub></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>l</mi><mi>o</mi><mi>s</mi><msub><mi>s</mi><mrow><mi>l</mi><mi>a</mi><mi>b</mi></mrow></msub></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>l</mi><mi>o</mi><mi>s</mi><msub><mi>s</mi><mrow><mi>l</mi><mi>c</mi><mi>h</mi></mrow></msub></mrow></semantics></math></inline-formula>. …”
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Study on Novel Surface Defect Detection Methods for Aeroengine Turbine Blades Based on the LFD-YOLO Framework by Wei Deng, Guixiong Liu, Jun Meng

“…The proposed approach employs the LDconv model to adjust the size and shape of convolutional kernels dynamically, integrates the deformable attention mechanism (DAT) to capture minute defect features effectively, and uses Focaler-CIoU to optimize the bounding box loss function of the detection network. …”
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Query-Based Instance Segmentation with Dual Attention Transformer for Autonomous Vehicles by Aya Taourirte, Li-Hong Juang

“…Finally, we incorporate the Complete IoU (CIoU) loss function to optimize object localization and improve prediction accuracy. …”
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Pedestrian detection method based on improved YOLOv5 by Shangtao You, Zhenchao Gu, Kai Zhu

“…Finally, a layer to increase the accuracy of detecting pedestrians at small scales. We optimize the regression prediction of the anchor using the Efficient IOU Loss (EIOU) function. …”
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Predicting the SYM‐H Index Using the Ring Current Energy Balance Mechanism by Lan Ma, Yong Ji, Chao Shen, Gang Zeng, Peng E, YanYan Yang, Shuo Ti, Nisar Ahmad

“…The fundamental form of the energy injection function is derived from existing solar wind–magnetosphere energy coupling functions, with its scale factor adjusted as a free‐fitting parameter to optimize the prediction of observations. …”
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Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…Secondly, as the model requires target recognition and segmentation of different types of tasks, an efficient layer aggregation network (RepGFPN) with skip layer connection structure is adopted to optimize the feature fusion part, greatly improving the detection accuracy of the model for different detection tasks while controlling the number of model parameters and inference speed; Finally, to address the detection tasks of three different label shapes, the Inner CIOU loss function is introduced to compensate for the weak generalization ability of the CIoU loss function in different detection tasks. …”
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Weekly Intraperitoneal Injection of Tamoxifen in an Inducible In Vivo Model of Junctional Epidermolysis Bullosa Generates Early and Advanced Disease Phenotypes by Eleri Mai Jones, Priya Garcha, Monique Aumailley, Edel Anne O’Toole, Emanuel Rognoni, Matthew Caley

“…Junctional epidermolysis bullosa caused by loss-of-function variants in genes encoding the skin basement membrane proteins laminin 332, type XVII collagen, or integrin α6β4 affects patients from birth with severe blistering, eventually leading to scarring and early lethality. …”
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Research on Wind Power Grid Integration Power Fluctuation Smoothing Control Strategy Based on Energy Storage Battery Health Prediction by Bin Cheng, Jiahui Wu, Guancheng Lv, Zhongbo Li

“…Secondly, based on the health prediction results, a control strategy based on the model predictive control (MPC) algorithm is proposed to manage the energy storage system’s charge/discharge process, ensuring that the power meets grid integration requirements while minimizing energy storage lifespan loss. Further, since the lifespan loss caused by smoothing the same fluctuation differs at different health levels, a fuzzy adaptive control strategy is used to adjust the parameters of the MPC algorithm’s objective function under varying health conditions, thereby optimizing energy storage power and achieving the smooth control of the wind farm grid integration power at different energy storage health levels. …”
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High accuracy identification of maize seed varieties based on a lightweight improved YOLOv8 by Siqi Niu, Xiaolin Xu, Ao Liang, Yuliang Yun, Fengqi Hao, Jinqiang Bai, Wenyi Sheng, Dexin Ma

“…Additionally, the Detect module was replaced with the improved Detect_EMA module, which efficiently retained information in each channel, reduced computational load, and more specifically optimized detection results. Lastly, the loss function was replaced with Inner_SIoU, which was more suitable for small-object detection tasks. …”
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LLD-YOLO: A Low-Light Object Detection Algorithm Based on Dynamic Weighted Fusion of Shallow and Deep Features by Wenhao Cai, Yajun Chen, Xiaoyang Qiu, Meiqi Niu, Jianying Li

“…To address these challenges, we propose an improved neck structure, SRB-FPN, to achieve fine-grained cross-level semantic alignment and feature fusion, while also optimizing the regression loss function to develop LLD-YOLO, a detector specifically designed for low-light conditions. …”
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Three-dimensional computer holography with phase space tailoring by Runze Zhu, Lizhi Chen, Jiasheng Xiao, Hao Zhang

“…This sampling ensures the reconstructed intensity distribution to be comprehensively constrained with physical consistency. A physics-informed loss function is constructed based on the phase space tailoring to optimize the CGH with suppression of vortex stagnation. …”
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A study on phonemes recognition method for Mandarin pronunciation based on improved Zipformer-RNN-T(Pruned) modeling. by Zhaohui Du, Xiaofeng Zhao, Lin Li, Baohua Yu, Lijiang Miao

“…Furthermore, a hybrid Pruned RNN-T/CTC Loss fusion strategy is proposed, further optimizing recognition performance. …”
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Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing. by Luigi Acerbi, Daniel M Wolpert, Sethu Vijayakumar

“…This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. …”
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Attention-enhanced StrongSORT for robust vehicle tracking in complex environments by Wei Xu, Xiaodong Du, Ruochen Li, Bingjie Li, Yuhu Jiao, Lei Xing

“…Abstract While multi-object tracking is critical for autonomous driving systems, traditional algorithms exhibit three fundamental limitations in complex scenarios: (1) blurred feature representation under occlusion and re-identification scenarios causing identity switches, (2) insufficient sensitivity to scale-variant targets due to fixed geometric constraints in conventional IoU-based loss functions, and (3) gradient degradation in deep convolutional layers hindering discriminative feature learning. …”
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Bayesian estimation strategy for multi-component geometric life testing model under doubly type-1 censoring scheme

“…The derivations of the Bayes estimators (BEs) and Bayes risks (BRs) are presented under square error loss function (SELF), precautionary loss function (PLF) and DeGroot loss function (DLF) using Beta prior under DT1CS. …”
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Specular Reflection Image Enhancement Based on a Dark Channel Prior by Ye Xin, Zhenhong Jia, Jie Yang, Nikola K. Kasabov

“…In this paper, we propose a specular highlight image enhancement algorithm based on a dark channel prior to solve the problem of information loss in specular highlight images in real scenes. …”
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A Hybrid Quantum-Classical Approach for Multi-Class Skin Disease Classification Using a 4-Qubit Model by Aravinda C V, Emerson Raja Joseph, Sultan Alasmari

“…We employ a class-weighted loss function with weights <inline-formula> <tex-math notation="LaTeX">$w_{y_{i}} = [{3.0, 3.5, 0.6, 0.4}]$ </tex-math></inline-formula> to address this imbalance, ensuring balanced representation across all classes. …”
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Detection Model for Cotton Picker Fire Recognition Based on Lightweight Improved YOLOv11 by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song, Yi Wu

“…To further improve localization performance and accelerate convergence, the loss function is also modified. These improvements enable the model to achieve higher precision in fire detection while ensuring fast and accurate localization. …”
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Key factors for the assessment of mobility in advanced dementia: A consensus approach by Karen Van Ooteghem, Kristin E. Musselman, Avril Mansfield, David Gold, Meghan N. Marcil, Ron Keren, Maria Carmela Tartaglia, Alastair J. Flint, Andrea Iaboni

“…The causes of decline are multifactorial, including disease‐specific changes in motor function, behavior, and cognition. To optimize clinical management of mobility, there is a need to better characterize capacity for safe and independent mobility. …”
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Node Classification Based on Kolmogorov-Arnold Networks by YUAN Lining, FENG Wengang, LIU Zhao

“…Thirdly, G-KAN maps the output to a probability distribution of labels using a linear layer and a Softmax function. Finally, the contrastive loss is used to optimize the output of the KAN layer, encouraging high-similarity nodes to be close to each other and low-similarity nodes to be far away. …”
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