DCPNet: Distribution Calibration Prototypical Network for Few-Shot Image Classification by Ranhui Xu, Kaizhong Jiang, Lulu Qi, Shaojie Zhao, Mingming Zheng

“…DCPNet incorporates a parallel hierarchical feature extraction module and a few-shot differentiation loss function to fine-tune the metric learning for better feature representation. …”
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Rotor angle stability enhancement using DDPG reinforcement agent with Gorilla troops optimized input scaling factors by Ahmed H. Yakout, Ahmed E. B. Abu-Elanien, Hany M. Hasanien

“…Abstract This paper introduces a Reinforcement Learning (RL)-based Power System Stabilizer (PSS) with a Deep Deterministic Policy Gradient (DDPG) algorithm for rotor angle stability. …”
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Optimization of D2D emergency communication resources for UAV relay based on DA-STD3 by Xiaofang Deng, Zijian Deng, Lin Zheng, Chao Yang, Chuanxu Chen

“…By designing the reward function and training mechanism, we can achieve good power control and reduce communication interference. …”
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Kolmogorov-Arnold Vision Transformer for Image Reconstruction in Lung Electrical Impedance Tomography by Ibrar Amin, Shuaikai Shi, Hasan AlMarzouqi, Zeyar Aung, Waqar Ahmed, Panos Liatsis

“…Electrical impedance tomography is a non-invasive and non-ionizing imaging technique, which can provide real-time monitoring of the internal structures and function of the human body, and has been particularly popular in lung monitoring. …”
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Preoperative submaximal cardiopulmonary exercise testing and its association with early postoperative complications by Zyad J. Carr, Jean Charchaflieh, Andres Brenes-Bastos, Hugo He, Hung-Mo Lin, Amanda Jankelovits, Emily Gu, Jill Zafar, Fed Ghali, Wei S. Tan, Paul Heerdt

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Unboxing Tree ensembles for interpretability: A hierarchical visualization tool and a multivariate optimal re-built tree by Giulia Di Teodoro, Marta Monaci, Laura Palagi

“…The interpretability of models has become a crucial issue in Machine Learning because of algorithmic decisions' growing impact on real-world applications. …”
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How to map soil organic carbon stocks at field scale in South Africa? by Willie Herman Cloete, Gerhard du Preez, George Munnik Van Zijl

“…For dry bulk density (ρb), a pedo-transfer function was created for predicting the ρb at unsampled locations. …”
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Search Guidance Network Assisted Dynamic Particle Swarm Optimization Algorithm by LIU Zhi, SONG Wei

“…Reinforcement learning is employed to obtain the desired output of the input particles and extreme learning machine is utilized to pre-train the network. …”
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AI Innovations in Liver Transplantation: From Big Data to Better Outcomes by Eleni Avramidou, Dominik Todorov, Georgios Katsanos, Nikolaos Antoniadis, Athanasios Kofinas, Stella Vasileiadou, Konstantina-Eleni Karakasi, Georgios Tsoulfas

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State Identification of Charging Module Based on SN‐EMD‐SSEE and DBO‐HKELM by Bingyu Li, Xianhai Pang, Xuhao Du, Ziwen Cai

“…However, the protection function of the charging module covers short fault, over‐voltage fault, and over‐current at system level rather than the open‐circuit fault of MOSFETs and diodes at component level, which leads to hidden fire danger or accident risks. …”
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Cross-Feature Hybrid Associative Priori Network for Pulsar Candidate Screening by Wei Luo, Xiaoyao Xie, Jiatao Jiang, Linyong Zhou, Zhijun Hu

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Lightweight coal mine conveyor belt foreign object detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…Lastly, the original CIoU loss function in Yolov8n is replaced with MPDIoU, which allows the model to more accurately predict the position and shape of bounding boxes in the object detection task, thereby further reducing accuracy loss. …”
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Cognitive load assessment through EEG: A dataset from arithmetic and Stroop tasksMendeley Data by Ali Nirabi, Faridah Abd Rahman, Mohamed Hadi Habaebi, Khairul Azami Sidek, Siti Yusoff

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Do STEM education problem-solving tasks trigger learners’ epistemic curiosity? And why we should be astonished by Sebastian Stuppan, Markus Rehm, Tessa J. P. van Schijndel, Markus Wilhelm

“…Tasks that build on each other and initiate a learning process are particularly effective. Tasks are often specified according to their function (confrontation, development, exercises, etc.). …”
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Post-translational regulation of stemness under DNA damage response contributes to the gingivobuccal oral squamous cell carcinoma relapse and progression by Sachendra Kumar, Annapoorni Rangarajan, Debnath Pal

“…The study indicates that loss-of-function in the identified MAPKAP1 somatic variant may promote stemness and elevated risk of relapse and disease progression in OSCC-GB under conditions of DDR in ‘With Tumor’ OSCC-GB, potentially contributing to increased mortality rates among Indian OSCC-GB patients.…”
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Real‐time object detection for unmanned vehicles in Bangladesh: Dataset, implementation and evaluation by Muhammad Liakat Ali, Topu Biswas, Shahin Akter, Mohammed Farhan Jawad, Hadaate Ullah

“…The MS COCO (Microsoft Common Objects in Context) dataset weights are included in the YOLOv5 deep learning network for transfer learning. Finally, Python TensorBoard was used to evaluate and visualize the model's performance. …”
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YOLO-ALW: An Enhanced High-Precision Model for Chili Maturity Detection by Yi Wang, Cheng Ouyang, Hao Peng, Jingtao Deng, Lin Yang, Hailin Chen, Yahui Luo, Ping Jiang

“…Additionally, the Wise-IoU (Wise Intersection over Union) loss function optimizes bounding box learning, further improving the detection of peppers in occluded or background-similar scenarios. …”
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Improved Multi-Size, Multi-Target and 3D Position Detection Network for Flowering Chinese Cabbage Based on YOLOv8 by Yuanqing Shui, Kai Yuan, Mengcheng Wu, Zuoxi Zhao

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Heart abnormality classification using ECG and PCG recordings with novel PJM-DJRNN by Nadikatla Chandrasekhar, Sujatha Canavoy Narahari, Sreedhar Kollem, Samineni Peddakrishna, Archana Penchala, Babji Prasad Chapa

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HMA-Net: a hybrid mixer framework with multihead attention for breast ultrasound image segmentation by Soumya Sara Koshy, L. Jani Anbarasi

“…Numerous computer-aided methods have been proposed for the segmentation of breast ultrasound images.MethodsA deep learning-based architecture utilizing a ConvMixer-based encoder and ConvNeXT-based decoder coupled with convolution-enhanced multihead attention has been proposed for segmenting breast ultrasound images. …”
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