Recent Advancement in Postharvest Loss Mitigation and Quality Management of Fruits and Vegetables Using Machine Learning Frameworks by Abha Singh, Gayatri Vaidya, Vishal Jagota, Daniel Amoako Darko, Ravindra Kumar Agarwal, Sandip Debnath, Erich Potrich

“…In this paper, we use Convolutional Neural Networks (CNNs)-based U-Net, DeepLab, and Mask R-CNN models to detect and predict postharvest deterioration zones in stored apple fruits. …”
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Development of Deep Learning Model for the Recognition of Cracks on Concrete Surfaces by Tien-Thinh Le, Van-Hai Nguyen, Minh Vuong Le

“…The developed model for the classification of images was based on a DL Convolutional Neural Network (CNN). To train and validate the CNN model, a database containing 40,000 images of concrete surfaces (with and without cracks) was collected from the available literature. …”
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A Health Status Identification Method for Rotating Machinery Based on Multimodal Joint Representation Learning and a Residual Neural Network by Xiangang Cao, Kexin Shi

“…First, vibration, acoustic, and image modal information is comprehensively utilized, which is extracted using a Gramian Angular Field (GAF), Mel-Frequency Cepstral Coefficients (MFCCs), and a Faster Region-based Convolutional Neural Network (RCNN), respectively, to construct a feature set. …”
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Reconstructing Evapotranspiration in British Columbia Since 1850 Using Publicly Available Tree-Ring Plots and Climate Data by Hang Li, John Rex

“…ET was estimated for the province of British Columbia in Canada from 1850 to 1981, using random forest, support vector machine, and convolutional neural network regressions. ET satellite images from 1982 to 2010 formed our dataset to train models for each vegetated pixel. …”
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Classification of English Words into Grammatical Notations Using Deep Learning Technique by Muhammad Imran, Sajjad Hussain Qureshi, Abrar Hussain Qureshi, Norah Almusharraf

“…The classification of parts of speech into different grammatical notations is the major problem that non-native English learners face. …”
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Channel computation based on multi-scale attention residual network by Wengang Li, Deli Zhou, Qiong Ye

“…The extracted features are then integrated and exploited through a residual convolutional architecture to derive an estimation of the channel matrix. …”
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Fault Diagnosis under Variable Working Conditions Based on STFT and Transfer Deep Residual Network by Yan Du, Aiming Wang, Shuai Wang, Baomei He, Guoying Meng

“…Unlike traditional deep convolutional neural network (DCNN) methods, by combining with transfer learning, the TDRN can make a bridge between two different working conditions, thereby using the knowledge learned from a working condition to achieve a high classification accuracy in another working condition. …”
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Intelligent SDN to enhance security in IoT networks by Safi Ibrahim, Aya M. Youssef, Mahmoud Shoman, Sanaa Taha

“…This paper proposes a framework for enhancing security in SDN by utilising three separate Deep Learning models, namely Deep Neural Network (DNN), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM). …”
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A real-time predicting online tool for detection of people’s emotions from Arabic tweets based on big data platforms by Naglaa Abdelhady, Ibrahim E. Elsemman, Taysir Hassan A. Soliman

“…For DL, three classifiers are applied: Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), and Bidirectional GRU (BiGRU). …”
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Multi-Dimensional Feature Fusion and Enhanced Attention Streaming Movie Prediction Algorithm by Hanqing Hu, Tianmu Tian, Chengjing Liu, Xueyuan Bai

“…Second, an attention mechanism was applied to dynamically assign importance to different time steps and features, enabling the model to focus on the most critical information based on time periods and movie types. …”
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DDoS attack detection in intelligent transport systems using adaptive neuro-fuzzy inference system by G. Usha, H. Karthikeyan, Kumar Gautam, Nikhil Pachauri

“…Moreover, Intelligent Transportation Systems is different from the standard vehicular ad hoc network design since it functions in a highly dynamic environment brought on by the quick mobility between the nodes in short connection times. …”
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Diagnostics of retinal pathologies by optical coherence tomography images using artificial intelligence tools by V. V. Neroev, A. A. Bragin, O. V. Zaytseva

“…The study used a dataset (20,000 eyes), publicly available on the Internet, which contains OCT images of healthy retina (5,000 eyes) and retina affected by three different pathologies (choroid neovascularization, macular edema, multiple drusen, 15,000 eyes). …”
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Fingerprint Classification Based on Multilayer Extreme Learning Machines by Axel Quinteros, David Zabala-Blanco

“…A brute-force heuristic optimization approach is applied to determine the hyperparameters that maximize classification accuracy across different M-ELM configurations while avoiding excessive training times. …”
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A model for tobacco growing area classification based on time series features of thermogravimetric analysis by Jiaxu Xia, Yunong Tian, Xianwei Hao, Yuhan Peng, Guanqun Luo, Zhihua Gan

“…By analyzing 375 tobacco samples from ten different provinces, CNN is employed to extract local features, while LSTM captures long-term dependencies in the DTG data. …”
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A novel hybrid model by integrating TCN with TVFEMD and permutation entropy for monthly non-stationary runoff prediction by Huifang Wang, Xuehua Zhao, Qiucen Guo, Xixi Wu

“…Then, the temporal convolutional network (TCN) model is built for runoff prediction for each high-frequency IMFs and the reconstructed low-frequency IMF respectively. …”
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Reservoir parameter prediction technology based on deep learning and its application in the Panyu 4 Sag, Pearl river mouth Bain by Yingwei Li, Yanhui Zhu, Zhenshen Li, Xiaozhao Zhang, Guofu Cai

“…To address this issue, this paper proposes a method using a convolutional neural network for predicting porosity and facies distribution. …”
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Multi-kernel inception-enhanced vision transformer for plant leaf disease recognition by Sk Mahmudul Hassan, Kumar Sekhar Roy, Ruhul Amin Hazarika, Mehbub Alam, Mithun Mukherjee

“…Most of these solutions with the standard convolutional neural network (CNN) approaches use uniform background laboratory setup leaf images to identify the diseases. …”
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Wearable Sensor-Based Behavioral User Authentication Using a Hybrid Deep Learning Approach with Squeeze-and-Excitation Mechanism by Sakorn Mekruksavanich, Anuchit Jitpattanakul

“…The suggested network design integrates convolutional neural networks for spatial feature extraction, while the SE blocks improve feature identification by flexibly recalibrating channel-wise feature responses. …”
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On Explainability of Reinforcement Learning-Based Machine Learning Agents Trained with Proximal Policy Optimization That Utilizes Visual Sensor Data by Tomasz Hachaj, Marcin Piekarczyk

“…It excels in the explanation process in a virtual simulation system based on a video system with relatively low resolution. Depending on the convolutional feature extractor of the PPO-trained neural network, our method obtains 0.945 to 0.968 accuracy of approximation of the black-box model. …”
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Modeling Equatorial to Mid‐Latitudinal Global Night Time Ionospheric Plasma Irregularities Using Machine Learning by Ephrem Beshir Seba, Giovanni Lapenta

“…We utilize Random Forest (RF) and a one‐dimensional Convolutional Neural Network (1D‐CNN) model, incorporating data from the Swarm A, B, and C satellites, space weather data from the OMNIWeb data center, as well as zonal and meridional wind model data. …”
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