Integration of wing pattern morphology and deep learning to support Plusiinae (Lepidoptera: Noctuidae) pest identification by Karina M. Torres, Chenjiao Tan, Kayla A. Mollet, Allan H. Smith-Pardo, Rui Xu, Changying Li, Silvana V. Paula-Moraes

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Enhanced Osteoporosis Detection Using Artificial Intelligence: A Deep Learning Approach to Panoramic Radiographs with an Emphasis on the Mental Foramen by Robert Gaudin, Wolfram Otto, Iman Ghanad, Stephan Kewenig, Carsten Rendenbach, Vasilios Alevizakos, Pascal Grün, Florian Kofler, Max Heiland, Constantin von See

“…A total of 250 PRs from three groups (A: osteoporosis group, B: non-osteoporosis group matching A in age and gender, C: non-osteoporosis group differing from A in age and gender) were cropped to the mental foramen region. A pretrained convolutional neural network (CNN) classifier was used for training, testing, and validation with a random split of the dataset into subsets (A vs. …”
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Explainable clinical diagnosis through unexploited yet optimized fine-tuned ConvNeXt Models for accurate monkeypox disease classification by Muhammad Waqar, Zeshan Aslam Khan, Shanzey Tariq Khawaja, Naveed Ishtiaq Chaudhary, Saadia Khan, Khalid Mehmood Cheema, Muhammad Farhan Khan, Syed Sohail Ahmed, Muhammad Asif Zahoor Raja

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A Power Monitor System Cybersecurity Alarm-Tracing Method Based on Knowledge Graph and GCNN by Tianhao Ma, Juan Yu, Binquan Wang, Maosheng Gao, Zhifang Yang, Yajie Li, Mao Fan

“…To this end, this paper proposes a power monitor system cybersecurity alarm-tracing method based on the knowledge graph (KG) and graph convolutional neural networks (GCNN). Specifically, a cybersecurity KG is constituted based on the historical alert, accurately representing the entities and relationships in massive alerts. …”
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Research on Predictive Analysis Method of Building Energy Consumption Based on TCN-BiGru-Attention by Sijia Fu, Rui Zhu, Feiyang Yu

“…This study proposes a Time Convolution Network model based on an attention mechanism, which combines the ability of the Time Convolution Network model to capture ultra-long time series information with the ability of the BiGRU model to integrate contextual information, improve model parallelism, and reduce the risk of overfitting. …”
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High-Concentration Time-Frequency Representation and Instantaneous Frequency Estimation of Frequency-Crossing Signals by Hui Li, Xiangxiang Zhu, Yingfei Wang, Xinpeng Cai, Zhuosheng Zhang

“…Finally, a comparison is performed against the short-time Fourier transform, synchrosqueezing transform, and convolutional neural network. Experimental validation shows that our proposed approach achieves high TF concentration, exhibiting robust noise immunity and enabling precise characterization of the time-varying law of frequency-crossing signals.…”
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HIDS-IoMT: A Deep Learning-Based Intelligent Intrusion Detection System for the Internet of Medical Things by Abdelwahed Berguiga, Ahlem Harchay, Ayman Massaoudi

“…The proposed model hybridizes the Convolutional Neural Network (CNN) for feature extraction and the Long Short Term Memory neural network (LSTM) for sequence data prediction. …”
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Current AI Applications and Challenges in Oral Pathology by Zaizhen Xu, Alice Lin, Xiaoyuan Han

“…Artificial intelligence (AI), particularly through machine learning (ML) and deep learning (DL) techniques such as convolutional neural networks (CNNs) and natural language processing (NLP), has shown remarkable promise in image analysis and clinical documentation in oral pathology. …”
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Occlusion Removal in Light-Field Images Using CSPDarknet53 and Bidirectional Feature Pyramid Network: A Multi-Scale Fusion-Based Approach by Mostafa Farouk Senussi, Hyun-Soo Kang

“…An architecture based on end-to-end learning is proposed to address this challenge that interactively combines CSPDarknet53 and the bidirectional feature pyramid network for efficient light-field occlusion removal. …”
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Optimizing Remote Sensing Image Retrieval Through a Hybrid Methodology by Sujata Alegavi, Raghvendra Sedamkar

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Speech-Controlled Robot Enabling Cognitive Training and Stimulation in Dementia Prevention for Severely Disabled People by Schewior Jonas, Grefen Roman, Verde Rodolfo, Ergardt Alina, Zhao Ying, Kullmann Walter H.

“…Speech recognition of the control commands is performed using a Convolutional Neural Network (CNN) based on the VGG- 16 architecture. …”
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Analyzing Expressions to Curate Feeds: A Real-Time Mood-Based Reels Algorithm by Isha Bhutto, Asad Ali Jatoi

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Deep Learning Approaches for Malware Detection: A Comprehensive Review of Techniques, Challenges, and Future Directions by Mohammad Alshoulie, Abid Mehmood

“…We analyze models based on Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and hybrid CNN-RNN architectures, evaluating their performance across publicly available datasets, including BIG2015, Malimg, Drebin, Malicia, and IoT-23. …”
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Deep learning and wavelet packet transform for fault diagnosis in double circuit transmission lines by Ziad M. Ali, Ehab M. Esmail

“…The approach is evaluated using multiple deep learning architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), and implemented in MATLAB. …”
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Fault Diagnosis Method for Open-circuit Faults in NPC Three-level Inverter based on WKCNN by Guozheng Zhang, Menghui Li, Xin Gu, Wei Chen

“…To address the challenges of fault feature extraction, this article proposes an end-to-end diagnostic approach based on a wavelet kernel convolutional neural network (WKCNN), capable of extracting multi-scale features from current signals to significantly enhance diagnostic accuracy. …”
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Artificial intelligence-powered innovations in periodontal diagnosis: a new era in dental healthcare by Jarupat Jundaeng, Jarupat Jundaeng, Jarupat Jundaeng, Rapeeporn Chamchong, Choosak Nithikathkul, Choosak Nithikathkul

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Comparison of Faster R-CNN and YOLOv5 for Overlapping Objects Recognition by Muhamad Munawar Yusro, Rozniza Ali, Muhammad Suzuri Hitam

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A Non-invasive Load Recognition Approach Incorporating SENet Attention Mechanism and GA-CNN by Xin SHEN, Gang WANG, Yitao ZHAO, Zhao LUO, Zhao LI, Xiaohua YANG

“…Firstly, the SENet attention mechanism is embedded in a convolutional neural network (CNN) to improve the characterizaion of key features and reduce feature redundancy. …”
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Automated image-based condition assessment of the built environment: A state-of-the-art investigation of damage characteristics and detection requirements by Leila Farahzadi, Ibrahim Odeh, Mahdi Kioumarsi, Behrouz Shafei

“…For the automated detection, localization, and measurement of damage, various convolutional neural network, support vector machine, and classification-based methods were examined, including their advantages and limitations. …”
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A review on amino acid based protein classification using supervised artificial intelligence (AI) models by Rida Zulfiqar, Talha Ahmed Khan, Abdullah Ayub Khan, Rubaika Akhtar, Sajid Ullah

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