A hybrid algorithmic model for enhancing security in intelligent reflecting surface-assisted wireless communication [0.03%]
一种用于增强智能反射表面辅助无线通信安全的混合算法模型
Sivasankar S,Markkandan S
Sivasankar S
This article introduces Synergistic Gradient Projection with Dynamic Adaptive Risk Expansion (SGP-DARE), a hybrid optimization framework designed to enhance physical-layer security in wireless networks supported by intelligent reflecting su...
A new era in identification of tick genera; artificial intelligence for precision and speed [0.03%]
蜱属鉴定的新时代；人工智慧助力精准与快速识别
Ibrahim A Ame,Abdullahi Ibrahim Umar,Cenk S Ozverel et al.
Ibrahim A Ame et al.
Background: The occurrence of pandemics in the last 20 years highlighted the unpreparedness of healthcare systems. There is a worldwide increased trend in the vector borne diseases. Ticks are one of the most common organi...
MS-YieldStackNet: multi-source data fusion for wheat yield estimation using a stacked ensemble neural network [0.03%]
基于堆叠集成神经网络的多源数据融合的小麦产量估算方法（MS-YieldStackNet）
Waqas Ali,Zeeshan Ramzan,Muhammad Shahbaz et al.
Waqas Ali et al.
Accurate crop yield prediction is vital for ensuring food security and informing agricultural policy, particularly in wheat-dependent regions like Pakistan where manual estimation methods are labor-intensive and imprecise. This study introd...
KomoTrip: a multi-day travel itinerary recommendation method based on the discrete komodo mlipir algorithm [0.03%]
基于离散科莫多蚂蚁算法的多日旅游行程推荐方法
Z K Abdurahman Baizal,Soni Fajar Surya Gumilang,Rio Nurtantyana et al.
Z K Abdurahman Baizal et al.
Technological developments in recent years led to the emergence of increasingly sophisticated recommender systems to support multi-day travel itineraries that fall under the Tourist Trip Design Problem (TTDP). Various problem analogies are ...
Robust coffee plant disease classification using deep learning and advanced feature engineering techniques [0.03%]
基于深度学习和先进特征工程技术的咖啡作物病害分类方法
Hanin Ardah,Maher Alrahhal,Walaa M Abd-Elhafiez et al.
Hanin Ardah et al.
Coffee, the world's most traded tropical crop, is vital to the economies of many producing countries. However, coffee leaf diseases pose a serious threat to coffee quality and sustainable production. Deep learning has shown strong performan...
Multimodal image fusion for enhanced vehicle identification in intelligent transport [0.03%]
增强智能交通中车辆识别的多模态图像融合技术
Naif Al Mudawi,Muhammad Waqas Ahmed,Haifa F Alhasson et al.
Naif Al Mudawi et al.
Target detection in remote sensing is essential for applications such as law enforcement, military surveillance, and search-and-rescue. With advancements in computational power, deep learning methods have excelled in processing unimodal aer...
Evaluating machine learning models for predictive accuracy in cryptocurrency price forecasting [0.03%]
评估机器学习模型在加密货币价格预测中的预测准确性
Shavez Mushtaq Qureshi,Atif Saeed,Farooq Ahmad et al.
Shavez Mushtaq Qureshi et al.
Our research investigates the predictive performance and robustness of machine learning classification models and technical indicators for algorithmic trading in the volatile cryptocurrency market. The main aim is to identify reliable appro...
AutoWIG: automatic generation of python bindings for C++ libraries [0.03%]
AutoWIG：C++库的Python绑定自动生成器
Pierre Fernique,Christophe Pradal
Pierre Fernique
Most of Python and R scientific packages incorporate compiled scientific libraries to speed up the code and reuse legacy libraries. While several semi-automatic solutions exist to wrap these compiled libraries, the process of wrapping a lar...
Zheng Xu,Gang Chen,Feng Li et al.
Zheng Xu et al.
Surface reconstruction is a foundational topic in computer graphics and has gained substantial research interest in recent years. With the emergence of advanced neural radiance fields (NeRFs) and 3D Gaussian splatting (3D GS), numerous inno...
A cluster-assisted differential evolution-based hybrid oversampling method for imbalanced datasets [0.03%]
一种基于群集的差分进化混合过采样方法处理类别不平衡数据集
Muhammed Abdulhamid Karabiyik,Bahaeddin Turkoglu,Tunc Asuroglu
Muhammed Abdulhamid Karabiyik
Class imbalance remains a significant challenge in machine learning, leading to biased models that favor the majority class while failing to accurately classify minority instances. Traditional oversampling methods, such as Synthetic Minorit...