Implementation of MF block in CNN for advanced REB fault diagnosis by M. Pandiyan, Narendiranath Babu T.

“…Using the Balance Cross-Entropy (BCE) loss function for training has helped the model optimize prediction accuracy by minimizing the difference between the actual class and the predicted class probabilities. …”
Get full text

YOLOrot2.0: A novel algorithm for high-precision rice seed size measurement with real-time processing by Jinfeng Zhao, Zeyu Hou, Qin Wang, Sheng Dai, Kaicheng Yong, Xuan Wang, Jiawen Yang, Qianlong Nie, Yan Ma, Xuehui Huang

“…To address these issues, YOLOrot2.0 introduces the following improvements: Firstly, it utilizes an anchor-free detection algorithm to optimize the detection of rotated targets. Secondly, the utilization of the Kalman Filter IoU loss function, which combines the horizontal bounding box and smooth L1 loss function, accelerates the convergence speed of the network. …”
Get full text

A study on Chinese language Cross-Modal pedestrian image information retrieval by Yan Xie, Jian Qu

“…Furthermore, we designed a novel MSWCMPME loss function to enhance the performance of our CMCPIR model by optimizing the fusion strategy for the outputs of image-text model. …”
Get full text

DSNET: A Lightweight Segmentation Model for Segmentation of Skin Cancer Lesion Regions by Yucong Chen, Guang Yang, Xiaohua Dong, Junying Zeng, Chuanbo Qin

“…Furthermore, we propose a boundary-interior correction loss function that focuses on both the boundary and the interior of the region, which effectively solves the dermatosis segmentation task for problems such as boundary blurring and interior missing. …”
Get full text

An Efficient Intersection Over Union Algorithm for 3D Object Detection by Sazan Ali Kamal Mohammed, Mohd Zulhakimi Ab Razak, Abdul Hadi Abd Rahman, Maria Abu Bakar

“…In this case, we propose a steady optimization procedure (SOP) for the EIoU loss to gradually approach the minimum value. …”
Get full text

Novel Custom Loss Functions and Metrics for Reinforced Forecasting of High and Low Day-Ahead Electricity Prices Using Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM)... by Ziyang Wang, Masahiro Mae, Takeshi Yamane, Masato Ajisaka, Tatsuya Nakata, Ryuji Matsuhashi

“…To implement this, we integrate these custom loss functions into a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model, augmented by an ensemble learning approach and multimodal features. …”
Get full text

Enhanced multi-level K-means clustering and cluster head selection using a modernized pufferfish optimization algorithm for lifetime maximization in wireless sensor networks by Anjana Koyalil, Sivacoumar Rajalingam

“…The test results show that the proposed strategy significantly improves the CH selection, increases the network lifetime by 12.5 % to 62.5 %, decreases the energy consumption by 16.5 % to 28.7 %, decreases the path loss by 16 % to 46 %, increases the number of alive nodes by 32.5 % to 55 %, increases the residual energy by 3.3 % to 77.7 %, decreases the cost function by 1.76 % to 4.42 %, and increases the normalized energy, compared to several benchmark techniques based on varying number of nodes and rounds.…”
Get full text

Isolation Enhancement Based on TM010 and TE30 Mode Characteristics in a Patch Antennas Using Genetic Algorithm Optimization for Ku-Band Applications by Muddineni Raveendra, U. Saravanakumar, P. Padmaloshani, P. Saam Prasanth Dheeraj, Anand Anbalagan, R. Sreelakshmy

“…The design utilized a Rogers 3003 series dielectric substrate with a dielectric constant of 3.3 and a loss tangent of 0.003. A genetic algorithm with tournament selection and a multiobjective function was applied to optimize key performance metrics, such as impedance matching, bandwidth, and gain. …”
Get full text

Thyristor Controlled Series Capacitor for Generation reallocation Using Firefly algorithm to avoid Voltage instability by Venkata Gundavarapu, Venkateswara Bathina

“…This Algorithm is implemented on multi objective function to obtain the Optimal Power Flow. The multi objective function consists of total real power loss, total voltage magnitude deviations, the fuel cost of total real power generation and the branch loading. …”
Get full text

Attention Mechanism and Weighted Trend Loss for Wind Speed Correction by Liu Xu, Yang Hao, Liang Xiaoyun, Chen Jing, Li Qiaoping, Li Ruqing, Chen Min

“…A new weighted trend-based mean squared error loss function is developed to optimize the correction process. …”
Get full text

Deep representation learning using layer-wise VICReg losses by Joy Datta, Rawhatur Rabbi, Puja Saha, Aniqua Nusrat Zereen, M. Abdullah-Al-Wadud, Jia Uddin

“…The architecture of the model is selected to be pyramidal, enabling effective feature extraction. In addition, we optimize weights for variance, invariance, and covariance terms of the loss function so that the model can capture higher-level semantic information optimally. …”
Get full text

Detection of human activities using multi-layer convolutional neural network by Essam Abdellatef, Rasha M. Al-Makhlasawy, Wafaa A. Shalaby

“…By leveraging advanced feature extraction and optimized learning strategies, the proposed model demonstrates its efficacy in achieving accuracy of 97.87%, 99.12%, 96.58%, and 98.51% for various human activities datasets; UCI-HAR, KU-HAR, WISDM, and HMDB51, respectively. …”
Get full text

Intelligent Wireless Power Scheduling for Lunar Multienergy Systems: Deep Reinforcement Learning for Real-Time Adaptive Beam Steering and Vehicle-to-Grid Energy Optimization by Thomas Tongxin Li, Shuangqi Li, Cynthia Xin Ding, Zhaoyao Bao, Mohannad Alhazmi

“…The reward function penalizes energy misallocation and misalignment losses while maximizing charging efficiency and systemwide energy resilience. …”
Get full text

Conditional GAN-Based Two-Stage ISP Tuning Method: A Reconstruction–Enhancement Proxy Framework by Pengfei Zhan, Jiongyao Ye

“…ReEn-GAN decouples the ISP process into two distinct stages: reconstruction (physical signal recovery) and enhancement (visual quality and color optimization). By employing distinct network architectures and loss functions tailored to specific objectives, the two-stage proxy can effectively optimize both the reconstruction and enhancement modules within the ISP pipeline. …”
Get full text

Scattering of Electromagnetic Waves by Loss and Gain Systems of Dielectric Resonators by A. A. Trubin

Get full text

Reservoir Stochastic Simulation Based on Octave Convolution and Multistage Generative Adversarial Network by Xuechao Wu, Wenyao Fan, Shijie Peng, Bing Qin, Qing Wang, Mingjie Li, Yang Li

“…Then, the octave convolution is used to perform multi-frequency feature representation on different feature maps. Finally, a joint loss function is defined to optimize network parameters to improve simulation qualities. …”
Get full text

A Faster, Integrated, and Trusted Certificate Authentication and Issuer Validation System Based on Blockchain by Rojalina Priyadarshini, Rhishav Pandey, K. C. Ankit, Deepesh Bhandari, Birendra Khadka, Rabindra Kumar Barik, Manob Jyoti Saikia

Get full text

POWER LOSSES ASSESSMENT IN TRANSFORMERS AFTER THE NORMATIVE OPERATING PERIOD by M. I. Fursanov, N. S. Petrashevich

“…Under the conditions of continued operation the power-losses measurement according to the functioning guidelines does not seem always possible.The authors present an improved power-losses assessment technique based on the currently accepted thermal model of the oil-transformer. …”
Get full text

Management options in the sudden hearing loss of a diabetic patient by Andreea Rusescu, Viorel Zainea, Oana Ruxandra Iana, Irina Ioniță, George Traian Alexandru Burcea-Dragomiroiu, Dragos Cristian Ștefănescu, Dumitru Cristinel Badiu, Florentina Gherghiceanu, Cătălina Pietroșanu, Corina Silvia Pop, Razvan Hainarosie, Mura Hainarosie

“…Adequate control of the progression, treatment and complications of diabetes mellitus ensures optimal treatment management in case of a sudden hearing loss and therefore interferes with the favorable functional hearing outcomes. …”
Get full text

Simultaneous distributed generation and electric vehicles hosting capacity enhancement through a synergetic hierarchical bi-level optimization approach based on demand response and... by Zenhom M. Zenhom, Shady H. E. Abdel Aleem, Essam Aboul Zahab, Tarek A. Boghdady

“…Nonetheless, the suggested multi-objective function—which includes DG-HC, EV-HC maximization, and loss minimization—is optimized by the DSO at the upper layer based on all of these optimal load curves. …”
Get full text