Efficient identification protocol provably secure in standard model by LI Yan-ping1, WANG Yu-min1

“…Based on the hardness assumption of the collusion attack algorithm with k traitors （K-CAA） in a gap Diffie-Hellman （GDH） group, a new and efficient identification protocol is proposed. The new identification protocol is proven secure against impersonation under concurrent reset attack setting in standard model. …”
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Efficient and accurate identification of maize rust disease using deep learning model by Pei Wang, Pei Wang, Jiajia Tan, Yuheng Yang, Yuheng Yang, Tong Zhang, Pengxin Wu, Xinglong Tang, Hui Li, Xiongkui He, Xinping Chen

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Efficient Wheat Disease Identification Using Hybrid Swin-SHARP Vision Model by Waqar Khalid, Yazeed Alkharijah, Syed Muhammad Usman, Shehzad Khalid

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Efficient Identification and Classification of Pear Varieties Based on Leaf Appearance with YOLOv10 Model by Niman Li, Yongqing Wu, Zhengyu Jiang, Yulu Mou, Xiaohao Ji, Hongliang Huo, Xingguang Dong

“…The accurate and efficient identification of pear varieties is paramount to the intelligent advancement of the pear industry. …”
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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…We have evaluated the accuracy of our proposed technique against state-of-the-art biomimetic computing models such as GA, PSO, GWO, DE, and ACO. While ACO achieved up to 89.45% accuracy, our Bayesian Optimization with LSTM outperformed all others, reaching a peak accuracy of 95.55%, demonstrating its effectiveness in enhancing spoken language identification. …”
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Advanced lightweight deep learning vision framework for efficient pavement damage identification by Shuai Dong, Yunlong Wang, Jin Cao, Jia Ma, Yang Chen, Xin Kang

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A Global Attention Mechanism-Based EfficientNet Model for Road Pavement-Type Identification by Zhe-Yuan Ni, Jun-Cheng Wang

“…Secondly, the EfficientNet-Global Attention Mechanism (GAM) model is developed through the integration of a GAM module into the EfficientNet architecture. …”
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Integrated Identification and Efficient Use of Biodiversity in Mountainous Regions by Mehdiyeva A. M., Mahmudova Z. A., Rustamova D. F., Mansurova D., Juraeva G.

“…The article studies the comprehensive identification and efficient use of biodiversity (geothermal sources) in mountainous regions. …”
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Identification of key parameter influence on efficiency of chain drive for track cycling − Preliminary results by Lanaspeze Gabriel, Best Martin, Guilbert Berengere, Cavoret Jérôme, Duval Arnaud, Manin Lionel, Ville Fabrice

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Efficient and rapid identification of tropical maize inbred lines tolerant to waterlogging stress by Sittal Thapa, Tosh Garg, Rumesh Ranjan, Gagandeep Singh, Yogesh Vikal

“…The use of BLPSI and ESIM selection indices as well as MTSI to judge the stability as well as genetic worth of genotypes further strengthens the selection efficiency. Lines thus performing best across all the models included I 185, I 172 and SE 503 and were identified as tolerant lines for WL. …”
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Gyroscope-Based Smartphone Model Identification via WaveNet and EfficientNetV2 Ensemble by Erkan Kiymik, Ali Emre Ozturk

“…A fine-tuned WaveNet model is employed to analyze the sequential nature of the gyroscope data, and an EfficientNetV2 model captures intricate time-frequency representations using Continuous Wavelet Transform (CWT) with the Morlet wavelet. …”
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Fast and lightweight automatic lithology recognition based on efficient vision transformer network by Yan Guo, Zhuowu Li, Fujiang Liu, Weihua Lin, Hongchen Liu, Quansen Shao, Dexiong Zhang, Weichao Liang, Junshun Su, Qiankai Gao

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Efficient Real-Time Isotope Identification on SoC FPGA by Katherine Guerrero-Morejón, José María Hinojo-Montero, Jorge Jiménez-Sánchez, Cristian Rocha-Jácome, Ramón González-Carvajal, Fernando Muñoz-Chavero

“…Efficient real-time isotope identification is a critical challenge in nuclear spectroscopy, with important applications such as radiation monitoring, nuclear waste management, and medical imaging. …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

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Efficient Structural Damage Detection with Minimal Input Data: Leveraging Fewer Sensors and Addressing Model Uncertainties by Fredi Alegría, Eladio Martínez, Claudia Cortés-García, Quirino Estrada, Andrés Blanco-Ortega, Mario Ponce-Silva

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Utilizing EfficientNet for sheep breed identification in low-resolution images by Galib Muhammad Shahriar Himel, Md. Masudul Islam, Mijanur Rahaman

“…We conducted experiments on the dataset using various EfficientNet models and found that EfficientNetB5 achieved the highest performance with 97.62 % accuracy on a 10 % test split. …”
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Efficient Convolutional Neural Network Model for the Taxonomy and Sex Identification of Three Phlebotomine Sandfly Species (Diptera, Psychodidae, and Phlebotominae) by Mohammad Fraiwan

“…In this paper, we develop a highly accurate and efficient convolutional network model that utilizes pharyngeal and genital images of sandfly samples to classify the sex and species of three sandfly species (i.e., <i>Phlebotomus sergenti</i>, <i>Ph. alexandri</i>, and <i>Ph. papatasi</i>). …”
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Identification of new inhibitors of the kinase acti­vity of CDK2 and CDK9 by molecular modeling and high-efficiency screening by G.V. Andrianov, I.G. Serebriiskii

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A task decomposition and scheduling model for power IoT data acquisition with overlapping data efficiency optimization by Jindong Cui, Yuqing Wang, Zengchen Zhu, Ruotong Li

“…Abstract To address the challenges of low efficiency and high redundancy in massive data acquisition within the Power Internet of Things (PIoT), existing systems suffer from redundant acquisition and resource waste due to insufficient identification of overlapping regions, while traditional scheduling mechanisms struggle to balance task priorities with dynamic scenario requirements. …”
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