Deep Learning Based Dual Channel Banana Grading System Using Convolution Neural Network by Raghavendra S, Souvik Ganguli, P. Thirumarai Selvan, Mitali Madhusmita Nayak, Sushovan Chaudhury, Randell U. Espina, Isaac Ofori

“…The invention of convolutional neural network (CNN) simplified the effort of feature engineering. …”
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Mathematical Modeling of Cyberattack Defense Mechanism Using Hybrid Transfer Learning With Snow Ablation Optimization Algorithm in Critical Infrastructures by Mohamad Khairi Ishak

“…For the cybersecurity classification process, the presented CDMHTL-SAOA technique applies the hybrid of convolutional neural network and bi-directional long short-term memory (CNN-BiLSTM) method. Eventually, the parameter choice of the CNN-BiLSTM technique has been implemented by the design of the hippopotamus optimization algorithm (HOA). …”
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Patient-Independent Epileptic Seizure Detection with Reduced EEG Channels and Deep Recurrent Neural Networks by Nadine El-Dajani, Tim Friedrich Lutz Wilhelm, Jan Baumann, Rainer Surges, Bernd T. Meyer

“…When using all channels of the 10–20 EEG cap system, the CNN-LSTM model achieved a sensitivity of 73%, with fewer than two seizures being falsely detected per hour. …”
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Low-Cost Driver Monitoring System Using Deep Learning by Hady A. Khalil, Sherif A. Hammad, Hossam E. Abd El Munim, Shady A. Maged

“…In addition to the deep learning CNN which runs on Raspberry Pi CPU, we utilize the Raspberry Pi GPU to run a head pose estimation algorithm to boost the system’s accuracy.…”
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Sentiment analysis of the Hamas-Israel war on YouTube comments using deep learning by Ashagrew Liyih, Shegaw Anagaw, Minichel Yibeyin, Yitayal Tehone

“…As a result, the Hybrid of CNN and Bi-LSTM with Word2vec achieved the highest performance with 95.73% accuracy for comments classifications.…”
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Optimasi Convolutional Neural Network Untuk Deteksi Covid-19 pada X-ray Thorax Berbasis Dropout by I Gede Totok Suryawan, I Putu Agus Eka Darma Udayana

“…Namun untuk melatih sebuah classifier CNN yang ampuh dan siap digunakan di dunia nyata membutuhkan computing power yang besar dan umumnya training rate yang lama.  …”
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Research on Urban Traffic Industrial Management under Big Data: Taking Traffic Congestion as an Example by Yi Zhang, Shuwang Yang, Hang Zhang

“…This paper establishes a prediction model of traffic flow, where three cycle dependent components are used to model three characteristics of traffic data, respectively. CNN is used to extract spatial features, and the combination of LSTM and attention mechanism is used to dynamically capture the influence of historical period on target period. …”
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Deep learning in gonarthrosis classification: a comparative study of model architectures and single vs. multi-model methods by Sahika Betul Yayli, Kutay Kılıç, Salih Beyaz

“…(2) How do seven convolutional neural network (CNN) architectures perform across four distinct deep learning tasks? …”
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Fully Automated Bone Age Assessment on Large-Scale Hand X-Ray Dataset by Xiaoying Pan, Yizhe Zhao, Hao Chen, De Wei, Chen Zhao, Zhi Wei

“…Besides, we choose a specific CNN to extract features and explain why we select that CNN. …”
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Enhanced detection of mild cognitive impairment in Alzheimer’s disease: a hybrid model integrating dual biomarkers and advanced machine learning by John Sahaya Rani Alex, R. Roshini, G. Maneesha, Jeetashree Aparajeeta, B. Priyadarshini, Chih-Yang Lin, Chi-Wen Lung

“…For this, a novel two-stage hybrid learning model that leverages 3D CNN and the notion of a Fuzzy and Machine learning model is proposed. …”
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Diagnosis of Coronary Heart Disease Through Deep Learning-Based Segmentation and Localization in Computed Tomography Angiography by Bo Zhao, Jianjun Peng, Ce Chen, Yongyan Fan, Kai Zhang, Yang Zhang

“…This research addresses these challenges by proposing TransCHD, a hybrid CNN-Transformer architecture developed for coronary artery segmentation in CCTA. …”
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Multi‐Wound Classification: Exploring Image Enhancement and Deep Learning Techniques by Prince Odame, Maxwell Mawube Ahiamadzor, Nana Kwaku Baah Derkyi, Kofi Agyekum Boateng, Kelvin Sarfo‐Acheampong, Eric Tutu Tchao, Andrew Selasi Agbemenu, Henry Nunoo‐Mensah, Dorothy Araba Yakoba Agyapong, Jerry John Kponyo

“…FixCaps had trainable parameters of about 8.28 MB compared with the 195.64 MB of the Gated Wavelet CNN Model.…”
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Learning Air Traffic as Images: A Deep Convolutional Neural Network for Airspace Operation Complexity Evaluation by Hua Xie, Minghua Zhang, Jiaming Ge, Xinfang Dong, Haiyan Chen

“…Motivated by the applications of deep learning network, the specific CNN model is introduced to automatically extract high-level traffic features from MTSIs and learn the SOC pattern. …”
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Convolutional neural networks for accurate real-time diagnosis of oral epithelial dysplasia and oral squamous cell carcinoma using high-resolution in vivo confocal microscopy by Rishi S. Ramani, Ivy Tan, Lindsay Bussau, Lorraine A. O’Reilly, John Silke, Christopher Angel, Antonio Celentano, Lachlan Whitehead, Michael McCullough, Tami Yap

“…The first CNN was used to filter for image quality, followed by image specific diagnostic triage models for fluorescein and acriflavine, respectively. …”
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GastroFuse-Net: an ensemble deep learning framework designed for gastrointestinal abnormality detection in endoscopic images by Sonam Aggarwal, Isha Gupta, Ashok Kumar, Sandeep Kautish, Abdulaziz S. Almazyad, Ali Wagdy Mohamed, Frank Werner, Mohammad Shokouhifar

“…To address these challenges, we introduced a specialized CNN-based architecture called GastroFuse-Net, designed to recognize human gastrointestinal diseases from endoscopic images. …”
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Profile to frontal face recognition in the wild using coupled conditional generative adversarial network by Fariborz Taherkhani, Veeru Talreja, Jeremy Dawson, Matthew C. Valenti, Nasser M. Nasrabadi

“…The authors have evaluated the performance of cpCNN and ADDA and compared it with the proposed cpGAN. …”
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Skin Lesion Classification Through Test Time Augmentation and Explainable Artificial Intelligence by Loris Cino, Cosimo Distante, Alessandro Martella, Pier Luigi Mazzeo

“…Our findings reveal that Test Time Augmentation enhances the balanced multi-class accuracy of CNN models by up to 0.3%, achieving a balanced accuracy rate of 97.58% on the International Skin Imaging Collaboration (ISIC 2019) dataset. …”
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Analysis of Feature Extraction and Anti-Interference of Face Image under Deep Reconstruction Network Algorithm by Jin Yang, Yuxuan Zhao, Shihao Yang, Xinxin Kang, Xinyan Cao, Xixin Cao

“…To explore the anti-interference performance of convolutional neural network (CNN) reconstructed by deep learning (DL) framework in face image feature extraction (FE) and recognition, in the paper, first, the inception structure in the GoogleNet network and the residual error in the ResNet network structure are combined to construct a new deep reconstruction network algorithm, with the random gradient descent (SGD) and triplet loss functions as the model optimizer and classifier, respectively, and it is applied to the face recognition in Labeled Faces in the Wild (LFW) face database. …”
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DEVELOPMENT OF A NIGERIAN CULTURAL ATTIRE RECOGNITION SYSTEM by OGUNBIYI DIMPLE, JIMOH KUDIRAT, ADEBAYO OLAJIDE, OKELOLA LOVELYN

“…Samples of clothing images depicting the cultural groups were obtained from publicly available online sources and an architecture to classify the images classes was designed using the Convolutional Neural Network (CNN) model. Performance evaluation results from experiment show that the model can classify images accordingly, achieving a validation accuracy score of 86 %. …”
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RESEARCH ON TRAFFIC CONGESTION DETECTION FROM CAMERA IMAGES IN A LOCATION OF DA LAT by Nguyen Thi Luong

“…This paper focuses on SVM, CNN, DenseNet, VGG, and ResNet models to detect traffic congestion from camera images collected at Nga 5 Dai Hoc, Da Lat. …”
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