A Noble Classification Framework for Data Glove Classification of a Large Number of Hand Movements by Yuhuang Zheng

“…The results of experiments using the Ninapro DB1 dataset demonstrate that our work can classify more types of hand movements than related algorithms with a precision of 93.15%.…”
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Rapid Classification and Treatment Algorithm of Cardiogenic Shock Complicating Acute Coronary Syndromes: The SAVE ACS Classification by Vasileios Panoulas, Charles Ilsley

“…A similar AUC was demonstrated in the validation cohort (AUC 0.815). Conclusions. …”
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Hybrid Method for Point Cloud Classification by Abdurrahman Hazer, Remzi Yildirim

“…Additionally, it demonstrates robust performance on the challenging ScanObjectNN dataset, with accuracies of 92% OA and 91.2% mAcc. …”
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An Efficient Detector for Automatic Tomato Classification Systems by Duy-Linh Nguyen, Xuan-Thuy Vo, Adri Priadana, Jehwan Choi, Kang-Hyun Jo

“…These results show that the proposed network is superior to others under a fixed set of experimental conditions. The video demonstration, datasets, weights, and models are available at <uri>https://bit.ly/3XdLrLM</uri>.…”
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Network representations of drum sequences for classification and generation by Daniel Gómez-Marín, Daniel Gómez-Marín, Sergi Jordà, Perfecto Herrera

“…Through a series of experiments, we demonstrate the effectiveness of this approach. First, we show that the complex network representation can accurately classify drum patterns into their respective musical styles, even with a limited number of training samples. …”
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Multiview Discriminative Geometry Preserving Projection for Image Classification by Ziqiang Wang, Xia Sun, Lijun Sun, Yuchun Huang

“…Experimental results on face recognition and facial expression recognition demonstrate the effectiveness of the proposed algorithm.…”
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Squeeze-and-Excitation Vision Transformer for Lung Nodule Classification by Xiaozhong Xue, Yanhe Ma, Weiwei Du, Yahui Peng

“…Finally, attention maps generated by Grad-CAM demonstrate that 2 attention mechanisms enable the model to focus on key areas for classifying benign and malignant lung nodules. …”
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Classification of ECG signals using deep neural networks by Nadour Mohamed, Cherroun Lakhmissi, Hadroug Nadji

“…The study's findings demonstrate that the GoogleNet, AlexNet and Resnet models achieve an impressive accuracy rate of 96%, 95,33% and 92,66%, in accurately predicting and classifying ECG signals associated with these cardiac conditions, respectively. …”
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Semantic Tokenization-Based Mamba for Hyperspectral Image Classification by Ri Ming, Na Chen, Jiangtao Peng, Weiwei Sun, Zhijing Ye

“…Finally, the fused semantic token is passed into a classifier for classification. Experimental results on three HSI datasets demonstrate that the proposed STMamba outperforms existing state-of-the-art deep learning and transformer-based methods.…”
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An Improved Feature Selection Based on Effective Range for Classification by Jianzhong Wang, Shuang Zhou, Yugen Yi, Jun Kong

“…Experiments on several well-known databases are performed to demonstrate the effectiveness of the proposed method.…”
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Optimized sequential model for superior classification of plant disease by Yogesh Chimate, Sangram Patil, K. Prathapan, Jaydeep Patil, Jayendra Khot

“…Our research, conducted on mango and groundnut leaves collected during field visits in western Maharashtra and supplemented by online datasets, demonstrates a CNN model that achieves an impressive 96% accuracy as compared to machine learning techniques that follow tedious feature extraction. …”
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Zero-Shot Classification of Art With Large Language Models by Tatsuya Tojima, Mitsuo Yoshida

“…Thus, it minimizes human costs. Our experiments demonstrated that the 4-bit quantized Llama-3 70B model, which can run on a local server, achieved the most accurate (over 0.9) automatic annotation of different art forms using LLMs, performing slightly better than the GPT-4o model from OpenAI. …”
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Explainable Security Requirements Classification Through Transformer Models by Luca Petrillo, Fabio Martinelli, Antonella Santone, Francesco Mercaldo

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Automated Classification of Glandular Tissue by Statistical Proximity Sampling by Jimmy C. Azar, Martin Simonsson, Ewert Bengtsson, Anders Hast

“…It is based on statistically representing the relative distribution of tissue components around lumen regions, while preserving spatial and quantitative information, as a basis for diagnosing and analyzing different areas within an image. We demonstrate the efficacy of the method in extracting discriminative features for obtaining high classification rates for tubular formation in both healthy and cancerous tissue, which is an important component in Gleason and tubule-based Elston grading. …”
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Urdu Toxic Comment Classification With PURUTT Corpus Development by Hafiz Hassaan Saeed, Tahir Khalil, Faisal Kamiran

“…Our extensive empirical validation demonstrates the superiority of the ensemble model, achieving a state-of-the-art F1-score of 91.65% on PURUTT, setting a benchmark F1-score on PURUTT corpus for Urdu toxic comment classification.…”
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Recognition and Classification of 3D Objects of Different Details by Islam A. Alexandrov, Maxim S. Mikhailov, Alexander N. Muranov, Vladimir Zh. Kuklin

“…This research demonstrates considerable potential for further development and application in the field of agriculture, underscoring the continued necessity for research in this area …”
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Density Classification with Non-Unitary Quantum Cellular Automata by Elisabeth Wagner, Federico Dell’Anna, Ramil Nigmatullin, Gavin K. Brennen

“…The second is a new quantum model that is designed to demonstrate additional quantum features and is restricted to only two-body interactions. …”
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Classification of Dyslexia Among School Students Using Deep Learning by Alia Hussein, Ahmed Talib Abdulameer, Ali Abdulkarim, Husniza Husni, Dalia Al-Ubaidi

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Mosaic-Mixed Attention-Based Unexpected Traffic Scene Classification by Sang-Hyun Lee, Soomok Lee, Ilsoo Yun

“…The detailed evaluation demonstrates improved efficiency and accuracy, underscoring the potential of the system for future traffic incident classification.…”
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An Enhanced Approach Using AGS Network for Skin Cancer Classification by Hwanyoung Lee, Seeun Cho, Jiyoon Song, Hoyoung Kim, Youjin Shin

“…The AGS network demonstrates how integrating diverse methods can improve the performance of skin cancer classification models.…”
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