A new CNN deep learning model for computer-intelligent color matching by He Zhibin, Tan Yanmei, Li Sa

“…To verify the performance of the proposed color-matching model, the superiority of the optimization algorithm (PSO) was first tested. The results showed that the accuracy of the PSO reached 98%, and the loss value of the algorithm function was only 0.02, significantly better than other algorithms. …”
Get full text

DHS-YOLO: Enhanced Detection of Slender Wheat Seedlings Under Dynamic Illumination Conditions by Xuhua Dong, Jingbang Pan

“…Third, we implement the ShapeIoU loss function that prioritizes geometric consistency between predicted and ground truth bounding boxes, particularly optimizing for slender plant structures. …”
Get full text

Bioengineering Tooth and Periodontal Organoids from Stem and Progenitor Cells by Fuad Gandhi Torizal, Syarifah Tiara Noorintan, Zakiya Gania

“…Tooth and periodontal organoids from stem and progenitor cells represent a significant advancement in regenerative dentistry, offering solutions for tooth loss and periodontal diseases. These organoids, which mimic the architecture and function of real organs, provide a cutting-edge platform for studying dental biology and developing therapies. …”
Get full text

Gas Detection and Classification Using Neural Network Based Gas Sensors by Munaf Ismail, Sri Arttini Dwi Prasetyowati

“…Alcoholic beverages, apart from being haram, also cause loss of consciousness. The influence of alcohol while driving is very dangerous and can result in an accident. …”
Get full text

Safety helmet detection methods in heavy machinery factory by Liu Baoju, Wei Xiangqian, Chen Qingshan, Liu Jiaqi, Chen Ye, Yu Peng, Lei shi, Hu Yongfeng

“…Additionally, the WIoU loss function is introduced to accelerate convergence and increase adaptability. …”
Get full text

A Method for Few-Shot Radar Target Recognition Based on Multimodal Feature Fusion by Yongjing Zhou, Yonggang Li, Weigang Zhu

“…Furthermore, we establish a multimodal fusion classification network that integrates bi-directional long short-term memory and residual neural network architectures, facilitating deep bimodal fusion through an encoding-decoding framework augmented by an energy embedding strategy. To optimize the model, we propose a cross-modal equilibrium loss function that amalgamates similarity metrics from diverse features with cross-entropy loss, thereby guiding the optimization process towards enhancing metric spatial discrimination and balancing classification performance. …”
Get full text

Research on action matching of skeletal point coordinates and sports teaching application based on Open-pose by Shunmin Su

“…Based on the Open-pose open source model, we construct a skeletal point coordinate action matching network model, use the feed-forward network for 2D confidence mapping, test it through the loss function, calculate the shortest distance to identify the association affinity domain, and introduce the greedy relaxation algorithm to optimize the accuracy rate of the association matching of multi-body skeletal points; we obtain the skeletal point coordinate parameters through the two-dimensional spatial mapping and use the k-means algorithm to quantify the features of the skeletal point coordinates, and the residuals of the skeletal point coordinates are quantized. …”
Get full text

The Development of a Lightweight DE-YOLO Model for Detecting Impurities and Broken Rice Grains by Zhenwei Liang, Xingyue Xu, Deyong Yang, Yanbin Liu

“…The ECANet module is introduced into the backbone feature extraction network, utilizing the weighted selection feature to cluster the network in the region of interest, enhancing attention to rice impurities and broken grains, and compensating for the reduced accuracy caused by model light weighting. The loss problem of class imbalance is optimized using the Focal Loss function. …”
Get full text

ADWNet: An improved detector based on YOLOv8 for application in adverse weather for autonomous driving by Xinyun Feng, Tao Peng, Ningguo Qiao, Haitao Li, Qiang Chen, Rui Zhang, Tingting Duan, JinFeng Gong

“…Simultaneously, to expedite the model's convergence, the bounding box's loss function has been optimized to SIoU loss. To elucidate the advantages of ADWNet in the context of adverse weather conditions, ablation studies and comparative experiments were conducted. …”
Get full text

Three-dimensional modeling of coupled momentum, heat, and mass transfer during potato frying: Effects of oil temperature, type, frying load, and fryer heating cycles by Jalal Dehghannya, Abdurrahman Ghaderi, Babak Ghanbarzadeh

“…The present study offers a mathematical model to optimize the frying process of potato slices by considering interactions between oil temperature (150, 170, 190 °C), oil type (canola, sunflower, and soybean), and frying load (potato/oil ratio: 1/10, 1/15, and 1/20) on the distribution of velocity, temperature, moisture loss, and oil absorption. …”
Get full text

Innovative multi-class segmentation for brain tumor MRI using noise diffusion probability models and enhancing tumor boundary recognition by Zengxin Liu, Caiwen Ma, Wenji She, Meilin Xie

“…Training is guided by a combined loss function, emphasizing Weighted Cross-Entropy and Weighted Dice Loss. …”
Get full text

Comparative Analysis of YOLO Models for Bean Leaf Disease Detection in Natural Environments by Diana-Carmen Rodríguez-Lira, Diana-Margarita Córdova-Esparza, José M. Álvarez-Alvarado, Julio-Alejandro Romero-González, Juan Terven, Juvenal Rodríguez-Reséndiz

“…In addition, we integrated the Sophia optimizer and PolyLoss function into YOLOv9e and enhanced it, providing even more accurate detection results. …”
Get full text

Neurodynamic robust adaptive UWB localization algorithm with NLOS mitigation by Yanxu Liu, Enwen Hu, Yudong Chen, Changyou Guo

“…Abstract For the robust localization in mixed line-of-sight (LOS) and non-line-of-sight (NLOS) indoor environments, we proposed a max-min optimization estimator from a measurement model and introduced an adaptive loss function to optimize the estimation. …”
Get full text

PdYOLO: A Lightweight Algorithm for Detecting Peach Fruits Against a Peach Tree Background by Jiajun Zhang, Jialin Zhang, Kazuki Kobayashi

“…First, the CIOU regression loss function in YOLOv8s is replaced with the WIoUv2 regression loss function, effectively alleviating the negative impact of uneven distribution of positive and negative samples during model training through a more balanced gradient gain distribution strategy, which significantly improves detection accuracy. …”
Get full text

A Method of Reducing Transmitting Delay for Balise in Train Control Simulation System by KE Changbo, XUE Renpu, YANG Kai

“…In the field of train control simulation test, balise interface adaptation of on-board equipment is an important function of train control simulation system. If the simulation system introduces too much delay, it will lead to on-board equipments receiving balise out of window. …”
Get full text

SR-YOLO: Spatial-to-Depth Enhanced Multi-Scale Attention Network for Small Target Detection in UAV Aerial Imagery by Shasha Zhao, He Chen, Di Zhang, Yiyao Tao, Xiangnan Feng, Dengyin Zhang

“…Finally, the model’s detection performance for small targets is improved by utilizing the Normalized Wasserstein Distance loss function to optimize the Complete Intersection over Union loss function. …”
Get full text

Delay-Sensitive Routing Schemes for Underwater Acoustic Sensor Networks by N. Javaid, M. R. Jafri, S. Ahmed, M. Jamil, Z. A. Khan, U. Qasim, S. S. Al-Saleh

“…These schemes also employ an optimal weight function ( W F ) for the computation of transmission loss and speed of received signal. …”
Get full text

Myocarditis Diagnosis Using Semi-Supervised Generative Adversarial Network and Differential Evolution by Haifeng Gui, Na Zhang

“…Additionally, a reconstruction loss is incorporated into the loss function of SS-GAN, compelling the generator to reconstruct outputs based on the discriminator's features, thereby aligning outputs closer to actual data configurations. …”
Get full text

Image captioning using bidirectional LSTM neural network by Farnaz Hoseini, Anaram Yaghoobi Notash

“…Performance is evaluated using Precision, Accuracy, Recall, F-score, and Loss Function metrics. Despite hardware limitations, the proposed BiLSTM model demonstrates a competitive accuracy of 75.90%, highlighting improvements in both performance and computational efficiency.…”
Get full text

Management of renal anemia by Amira Peco-Antic

“…Other reasons include reduced red blood cell lifespan, chronic blood loss, iron deficiency, inhibitors of erythropoiesis, and malnutrition. …”
Get full text