Enhancing maize LAI estimation accuracy using unmanned aerial vehicle remote sensing and deep learning techniques by Zhen Chen, Weiguang Zhai, Qian Cheng

“…Therefore, this study evaluates the potential of multi-source feature fusion and convolutional neural networks (CNN) in estimating maize LAI. …”
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CFNN for Identifying Poisonous Plants by Israa Mohammed Hassoon, Shaymaa Akram Hantoosh

“…Combination of shape features and statistical features are extracted from leaf then fed to cascade-forward neural network which used TRAINLM function for training. 500 samples of leaf images are used, 250 samples are poisonous, the remaining 250 samples are non-poisonous.300 samples used in training, 200 samples for testing. …”
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Multi-Level Intertemporal Attention-Guided Network for Change Detection in Remote Sensing Images by Shuo Liu, Qinyu Zhang, Yuhang Zhang, Xiaochen Niu, Wuxia Zhang, Fei Xie

“…To address this issue, we proposed a Multi-level Intertemporal Attention-guided Network (MIANet) for CD. Firstly, an Intertemporal Fusion Attention Unit (IFAU) is proposed to facilitate early feature interaction, which helps eliminate irrelevant changes. …”
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Computing the Deep Semantics of Visual Communications by Trpimir Jeronim Ježić, Marko Maričević, Ivana Pavlović, Miroslav Mikota

Subjects: “…convolutional neural networks…”
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A Comparative Analysis of QoS, GoS, and QoE Metrics in Network Performance Evaluation by V. A. Gasimov, L. R. Zeynalli-Huseynzade, G. A. Zahidova

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Network assortativity for a multidimensional evaluation of socio-economic territorial biases in university rankings. by Loredana Bellantuono, Andrea Lo Sasso, Nicola Amoroso, Alfonso Monaco, Sabina Tangaro, Roberto Bellotti

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Spatial Shape-Aware Network for Elongated Target Detection by Shaowen Xu, Der-Horng Lee

“…To overcome these challenges, we propose a novel Spatial Shape-Aware Network for Elongated Target Detection. Specifically, we introduce three key modules: a Boundary-Guided Spatial Feature Perception Module (BGSF), a Shape-Sensing Module (SSM), and a Potential Evaluation Module (PEM). …”
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Leveraging data analytics for detection and impact evaluation of fake news and deepfakes in social networks by Tony Mathew Abraham, Tao Wen, Ting Wu, Yu-wang Chen

“…Additionally, a convolutional neural network model is designed to detect deepfake images with two distinct architectures, namely, ResNet50 and DenseNet121. …”
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Secure and efficient cloudlet networks: blockchain integration with agent-based proof of trust mechanism by Nothile C. Masango, Jeffrey O. Agushaka, Mercy C. Amaefule, Olutosin Taiwo, Peiying Zhang, Absalom E. Ezugwu, Kashif Saleem, Aseel Smerat, Laith Abualigah

“…This paper presents a novel approach to addressing these challenges by integrating blockchain technology with cloudlet networks, bolstered by an agent-layer concept. The proposed architecture features an agent between mobile devices and cloudlets, utilizing a unique "proof of trust" consensus mechanism. …”
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Enhancing Neural Network Interpretability Through Deep Prior-Guided Expected Gradients by Su-Ying Guo, Xiu-Jun Gong

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Multi-Scale Feature Fusion Model for Bridge Appearance Defect Detection by Rong Pang, Yan Yang, Aiguo Huang, Yan Liu, Peng Zhang, Guangwu Tang

“…Accordingly, a novel Lightweight MFF (namely MFF-L）model for bridge appearance defect detection using a lightweight network EfficientNetV2 and a feature pyramid network is proposed, which fuses multi-scale features to shorten the training speed and improve recognition accuracy. …”
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A Deep Learning Architecture for Land Cover Mapping Using Spatio-Temporal Sentinel-1 Features by Luigi Russo, Antonietta Sorriso, Silvia Liberata Ullo, Paolo Gamba

“…Deep learning (DL), particularly convolutional neural networks (CNNs) and vision transformers (ViTs), have revolutionized this field by enhancing the accuracy of classification tasks. …”
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Classification of arteriovenous fistula sounds using a convolutional block attention module and long short-term memory neural network by Jun Zhang, Rongxi Zhang, Xinming Shu, Hongtao Zhang

“…Features were extracted by combining Mel-Frequency Cepstral Coefficients with Mel-Spectrogram data, generating a novel set of feature parameters. …”
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Intelligent text analysis for effective evaluation of english Language teaching based on deep learning by Yuan Ren, Wenjuan Fan, Jinhai Wang

“…Building on traditional deep neural networks (DNNs), the model incorporates text structure features and attention mechanisms, while adversarial training is employed to optimize feature extraction and enhance cross-prompt adaptability. …”
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Swift prediction of personalized head and chest organ doses from CT examinations via neural networks with optimized quantity of hidden layers and radiomics features by Wencheng Shao, Xin Lin, Ying Huang, Liangyong Qu, Weihai Zhuo, Haikuan Liu

“…Objective: To utilize radiomics features to enhance the prediction of personalized organ doses from CT scans, in order to explore methods for improving neural network-based models. …”
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Operation standardization evaluation method based on improved YOLOv8n for ship equipment disassembly and assembly by Zhendong ZHANG, Cong GUAN, Zehui ZHANG, Chao WU, Xuewen DING

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Software Defect Prediction Based on Effective Fusion of Multiple Features by Chaozheng Zhang, Junhua Wu

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Remote sensing image interpretation of geological lithology via a sensitive feature self-aggregation deep fusion network by Kang He, Jie Dong, Haozheng Ma, Yujie Cai, Ruyi Feng, Yusen Dong, Lizhe Wang

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Advanced hybrid deep learning model for enhanced evaluation of osteosarcoma histopathology images by Arezoo Borji, Arezoo Borji, Arezoo Borji, Gernot Kronreif, Bernhard Angermayr, Bernhard Angermayr, Sepideh Hatamikia, Sepideh Hatamikia

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MSF-ACA: Low-Light Image Enhancement Network Based on Multi-Scale Feature Fusion and Adaptive Contrast Adjustment by Zhesheng Cheng, Yingdan Wu, Fang Tian, Zaiwen Feng, Yan Li

“…To address the issues of loss of important detailed features, insufficient contrast enhancement, and high computational complexity in existing low-light image enhancing methodologies, this paper presents a low-light image enhancement network (MSF-ACA), which uses multi-scale feature fusion and adaptive contrast adjustment. …”
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