Leveraging transformer models to predict cognitive impairment: accuracy, efficiency, and interpretability by Kai Ma, Junzhi Zhang, Xinhang Huang, Mengyang Wang

“…Conclusion The enhanced Transformer model offers superior accuracy and efficiency in predicting cognitive decline compared to traditional models. …”
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Linear viscoelastic models from creep and complex modulus testing in soil-emulsion by Paulo Mateus Barros Rodrigues, Silvrano Adonias Dantas Neto, Lucas Feitosa de Albuquerque Lima Babadopulos, Jorge Luiz Oliveira Lucas Júnior

“…Test samples were then exposed to air until a constant density loss was detected, followed by conducting complex modulus tests at thirty different temperature-frequency pairs. …”
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Accurate depth of anesthesia monitoring based on EEG signal complexity and frequency features by Tianning Li, Yi Huang, Peng Wen, Yan Li

“…A random forest regression model was employed to estimate anesthetic states, and an unsupervised learning method using the Hurst exponent algorithm and hierarchical clustering was introduced to detect transitions between anesthesia states. The method was tested on two independent datasets (UniSQ and VitalDB), achieving an average Pearson correlation coefficient of 0.86 and 0.82, respectively. …”
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Improving Computational Efficiency in Monte Carlo Simulation for Radiation Portal Monitor by Sim Hayoung, Seo Hee

“…In the present study, the applicability of the various techniques to improve calculation efficiency was evaluated. For example, as a simple but highly effective way, a simple box was used to surround the complex geometry of the RPM, resulting in 1.75 times of improvement in the calculation efficiency. …”
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DANNET: deep attention neural network for efficient ear identification in biometrics by Deepthy Mary Alex, Kalpana Chowdary M., Hanan Abdullah Mengash, Venkata Dasu M., Natalia Kryvinska, Chinna Babu J., Ajmeera Kiran

“…Despite numerous proposed convolutional neural network (CNN) based deep learning techniques for ear detection, achieving the expected efficiency and accuracy remains a challenge. …”
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L-ENet: An Ultralightweight SAR Image Detection Network by Yutong Wang, Min Miao, Shiliang Zhu

“…Synthetic aperture radar imagery plays a vital role in maritime vessel detection, despite facing challenges like complex marine environments, low-contrast target recognition, and similarities between ships and sea surface waves. …”
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Efficient Onboard Multitask AI Architecture Based on Self-Supervised Learning by Gabriele Inzerillo, Diego Valsesia, Enrico Magli

“…Experiments on three sample tasks of cloud segmentation, flood detection, and marine debris classification on a 7-W embedded system show competitive results with inference quality close to high-complexity state-of-the-art models and high throughput in excess of 8 Megapixel/s.…”
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Spectral Efficient Asymmetrically Clipped Hybrid FBMC for Visible Light Communication by Sanjeev Kumar, Preeti Singh

“…The analytical performance of the proposed technique is compared using parameters, namely, bit error rate (BER), spectral efficiency, computational complexity, and peak to average power ratio (PAPR). …”
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Novel Intermode Prediction Algorithm for High Efficiency Video Coding Encoder by Chan-seob Park, Gwang-Soo Hong, Byung-Gyu Kim

“…Moreover, in order to speed up the encoding time, the efficient merge SKIP detection method is developed additionally based on the contextual mode information of neighboring CUs. …”
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GE-YOLO for Weed Detection in Rice Paddy Fields by Zimeng Chen, Baifan Chen, Yi Huang, Zeshun Zhou

“…Weeds are a significant adverse factor affecting rice growth, and their efficient removal necessitates an accurate, efficient, and well-generalizing weed detection method. …”
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Spatial heterogeneity and peptide availability determine CTL killing efficiency in vivo. by Thea Hogan, Ulrich Kadolsky, Sim Tung, Benedict Seddon, Andrew Yates

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Tennis ball detection based on YOLOv5 with tensorrt by Xiulei Zhang, Bin Li

“…First, YOLOv5 is used for target detection to achieve efficient tennis feature extraction. …”
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Efficient CNN architecture with image sensing and algorithmic channeling for dataset harmonization by Khadija Kanwal, Khawaja Tehseen Ahmad, Aiza Shabir, Li Jing, Helena Garay, Luis Eduardo Prado Gonzalez, Hanen Karamti, Imran Ashraf

“…The goal targets compact efficient image feature vectors that process data in parallel regardless of input color or grayscale consistency and work across different datasets and semantic categories. …”
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Interpretable Deep Learning for Efficient Code Smell Prioritization in Software Development by Maaeda M. Rashid, Mohd Hafeez Osman, Khaironi Yatim Sharif, Hazura Zulzalil

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Parameter Adaptive LCD Screen Defect Detection Framework by LIU Wang, SHAO Huili, HE Yongjun, XIE Yining, CHEN Deyun

“…It is necessary to detect defects in the production process of LCD screens for quality improvements Manual detection brings a heavy workload and low accuracy Therefore, an efficient and accurate automatic detection method is urgently needed To this end, this paper proposes a new defect detection framework, which mainly includes screen area extraction, preprocessing, threshold segmentation and defect selection By adaptive adjustment of parameters, the detection method can adapt to various complex situations In order to eliminate the influence of illumination changes, the defect region is segmented by automatic parameter adjustment in the threshold segmentation First, the maximum grayscale value of the image is calculated, and then the fixed parameters and the coefficient of the defect image are determined according to the nodefect image, and finally the maximum value which was selected as the minimum threshold of the threshold segmentation from the fixed parameters and the product of the maximum grayscale value and the coefficient In addition, in order to solve the problem that the brightness difference of the images captured by lowresolution cameras is too small to detect defects in the saturation condition, selfadaptive adjustment of exposure parameters was used to collect images to process different parts of images with large difference in light and shade Experiments show that the method can achieve high performance and efficiency in detecting defects such as points, lines, Mura, saturation…”
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Effects of feature selection and normalization on network intrusion detection by Mubarak Albarka Umar, Zhanfang Chen, Khaled Shuaib, Yan Liu

“…The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence (AI) techniques (such as machine learning (ML) and deep learning (DL)) to build more efficient and reliable intrusion detection systems (IDSs). …”
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Vision transformers for automated detection of pig interactions in groups by Gbadegesin Taiwo, Sunil Vadera, Ali Alameer

“…The model's ability to recognize contextual spatial data enables strong detection even in complex contexts, due to the use of Gaussian Error Linear Unit (GELU) an activation function responsible for introduction of non-linear data to the model and Multi Head Attention feature that ensures all relevant details contained in a data are captured in Vision Transformer. …”
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Advances in electrochemical biosensors for the detection of tumor-derived exosomes by Jun Chen, Zhou Zhao, Honglin Zhu, Xiaobing Li

“…Nevertheless, the nanoscale size and relatively low abundance of exosomes, as well as complex body liquid matrix pose daunting challenges for efficient isolation and sensitive detection of T-EXOs. …”
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Defects Localization and Classification Method of Power Transmission Line Insulators Aerial Images Based on YOLOv5 EfficientNet and SVM by Lin Li, Qiaoling Yin, Xiaofeng Wang, Hang Wang

“…However, existing methods face challenges in achieving satisfactory accuracy, particularly in complex environments. Moreover, previous approaches primarily focus on detecting a single type of insulator defect without further categorizing them. …”
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Research on Improved YOLOv7 for Traffic Obstacle Detection by Yifan Yang, Song Cui, Xuan Xiang, Yuxing Bai, Liguo Zang, Hongshan Ding

“…However, there is limited research on traffic obstacle detection in complex scenarios involving road construction and sudden accidents. …”
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