Computer-Aided Brain Tumor Diagnosis: Performance Evaluation of Deep Learner CNN Using Augmented Brain MRI by Asma Naseer, Tahreem Yasir, Arifah Azhar, Tanzeela Shakeel, Kashif Zafar

“…Analysing Magnetic Resonance Images (MRIs) manually is inadequate for efficient and accurate brain tumor diagnosis. …”
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Deception detection based on micro-expression and feature selection methods by Shusen Yuan, Zilong Shao, Zhongjun Ma, Ting Cao, Hongbo Xing, Yong Liu, Yewen Cao

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A publicly available pharyngitis dataset and baseline evaluations for bacterial or nonbacterial classification by Negar Shojaei, Habib Rostami, Mohammad Barzegar, Shokooh Saadat Farzaneh, Zohreh Farrar, Majid Alimohammadi, Jahanbakhsh Keyvani, Mehdi Mirzad, Leila Gonbadi

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PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell by Xin Shi, Qing Huang, Teng Xu, Hongwen Mei, Tingwei Quan, Xiuli Wang, Yinghan Shi, Ye Hu, Zhimei Duan, Fei Xie, Sifan Li, Lixin Xie, Kaifei Wang

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I know your stance! Analyzing Twitter users’ political stance on diverse perspectives by Jisu Kim, Dongjae Kim, Eunil Park

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Truth be told: a multimodal ensemble approach for enhanced fake news detection in textual and visual media by Rami Mohawesh, Islam Obaidat, Ahmed Abdallah AlQarni, Ali Abdulaziz Aljubailan, Moy’awiah A. Al-Shannaq, Haythem Bany Salameh, Ali Al-Yousef, Ahmad A. Saifan, Suboh M. Alkhushayni, Sumbal Maqsood

“…Similarly, uses the ResNet model, a deep convolutional neural network known for its efficacy in image feature extraction and recognition, to derive a feature vector from the image(s) in the new article. then combines these generated vectors using a weighted fusion strategy to obtain a unified feature representation capturing nuances from both textual and visual data. …”
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Encoder embedding for general graph and node classification by Cencheng Shen

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SMART CONTROL OF WIND-FED BLDC MOTOR DRIVES THROUGH IOT AND SIX-STEP INVERTER TECHNIQUE by K Subha Sharmini, R Vinodha, T Porselvi, K Padmanaban, Minakshi Sanadhya

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Regularity in Vague Intersection Graphs and Vague Line Graphs by Muhammad Akram, Wieslaw A. Dudek, M. Murtaza Yousaf

“…Fuzzy graph theory is commonly used in computer science applications, particularly in database theory, data mining, neural networks, expert systems, cluster analysis, control theory, and image capturing. …”
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A disentangled generative model for improved drug response prediction in patients via sample synthesis by Kunshi Li, Bihan Shen, Fangyoumin Feng, Xueliang Li, Yue Wang, Na Feng, Zhixuan Tang, Liangxiao Ma, Hong Li

“…DiSyn uses a domain separation network (DSN) to disentangle drug response related features, employs data synthesis technology to increase the sample size and iteratively trains for better feature disentanglement. …”
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Perceptual design method for smart industrial robots based on virtual reality and synchronous quantitative physiological signals by Wangqun Xiao, Jianxin Cheng

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ACtriplet: An improved deep learning model for activity cliffs prediction by in tegrating triplet loss and pre-training by Xinxin Yu, Yimeng Wang, Long Chen, Weihua Li, Yun Tang, Guixia Liu

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Research and Design of an Airfield Runway FOD Detection System Based on WSN by Li Ang

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Deep learning-based tumor segmentation and radiogenomic model for predicting EGFR amplification and assessing intratumoural heterogeneity in glioblastoma by Jianpeng Liu, Chuyun Shen, Shufan Jiang, Yanfei Wu, Jiaqi Tu, Yifang Bao, Haiqing Li, Na Wang, Ying Liu, Ji Xiong, Xueling Liu, Yuxin Li

“…Results The segmentation performance was validated on two independent validation cohorts, achieving a mean DSC of 0.952 ± 0.026 and 0.961 ± 0.034, respectively.1409 radiomics features were respectively extracted from the the contrast-enhanced T1-weighted imaging images, thirty-seven signatures were identified through feature selection, leading to the development of a robust classification model. …”
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Dependency-Aware Entity–Attribute Relationship Learning for Text-Based Person Search by Wei Xia, Wenguang Gan, Xinpan Yuan

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Self-Supervised Learning to Unveil Brain Dysfunctional Signatures in Brain Disorders: Methods and Applications by Ying Li, Yanwu Yang, Yuchu Chen, Chenfei Ye, Ting Ma

“…Highlight: This paper provides a comprehensive overview of SSL techniques applied to functional neuroimaging data, such as functional magnetic resonance imaging and electroencephalography, with a specific focus on their applications in various neuropsychiatric disorders. …”
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Incorporating Crowdsourced Annotator Distributions into Ensemble Modeling to Improve Classification Trustworthiness for Ancient Greek Papyri by Graham West, Matthew I. Swindall, Ben Keener, Timothy Player, Alex C. Williams, James H. Brusuelas, John F. Wallin

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Unsupervised clustering based coronary artery segmentation by Belén Serrano-Antón, Manuel Insúa Villa, Santiago Pendón-Minguillón, Santiago Paramés-Estévez, Alberto Otero-Cacho, Diego López-Otero, Brais Díaz-Fernández, María Bastos-Fernández, José R. González-Juanatey, Alberto P. Muñuzuri

“…This paper proposes an automatic segmentation methodology based on clustering algorithms and a graph structure, which integrates data from both the clustering process and the original images. …”
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Robust People Tracking Using an Adaptive Sensor Fusion between a Laser Scanner and Video Camera by Yeong Nam Chae, Yeong-Jae Choi, Yong-Ho Seo, Hyun S. Yang

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Evaluation Metrics and Methods for Generative Models in the Wireless PHY Layer by Michael Baur, Nurettin Turan, Simon Wallner, Wolfgang Utschick

“…Moreover, we propose an application cross-check to evaluate the generative model’s samples for training machine learning-based models in relevant downstream tasks. Our analysis is based on real-world measurement data and includes the Gaussian mixture model, variational autoencoder, diffusion model, and generative adversarial network. …”
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