UNIFIED MULTIMODAL BIOMETRICS FUSION USING DEEP LEARNING FOR SECURING IOT by Prabhjot Kaur, Chander Kaur

“…In this work undertakes a comparative analysis to appraise the performance of the different CNN architectures and fusion techniques under scrutiny. …”
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Screen shooting resistant watermarking based on cross attention by Lianshan Liu, Peng Xu, Qianwen Xue

“…Most existing solutions are based on Convolutional Neural Networks (CNNs) for the embedding of watermarks. …”
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Plasmonic coffee-ring biosensing for AI-assisted point-of-care diagnostics by Kamyar Behrouzi, Zahra Khodabakhshi Fard, Chun-Ming Chen, Peisheng He, Megan Teng, Liwei Lin

“…We tested four different proteins, Procalcitonin (PCT) for sepsis, SARS-CoV-2 Nucleocapsid (N) protein for COVID-19, Carcinoembryonic antigen (CEA) and Prostate-specific antigen (PSA) for cancer diagnosis, showing a working concentration range over five orders of magnitude. …”
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Incorporating Attention Mechanism Into CNN-BiGRU Classifier for HAR by Ohoud Nafea, Wadood Abdul, Ghulam Muhammad

“…The proposed methodology uses convolutional neural networks (CNN) and recurrent neural networks (RNN) to extract the spatial and temporal features. …”
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A hybrid learning approach for MRI-based detection of alzheimer’s disease stages using dual CNNs and ensemble classifier by Sepideh Zolfaghari, Atra Joudaki, Yashar Sarbaz

“…Initially, these images were resized and augmented before being input into Network 1 and Network 2, which have different structures and layers to extract important features. …”
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Utilizing EfficientNet for sheep breed identification in low-resolution images by Galib Muhammad Shahriar Himel, Md. Masudul Islam, Mijanur Rahaman

“…The classification model we developed has the potential to assist sheep farmers in efficiently distinguishing between different breeds, facilitating more precise assessments and sector-specific classification for various businesses within the industry.…”
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Application of CNN and MLP models for structural health monitoring: A case study on Saigon Bridge by Thanh Q Nguyen, Tu B Vu, Niusha Shafiabady, Thuy T Nguyen, Phuoc T Nguyen

“…Additionally, extending the scope of our research to encompass different bridge types and environmental conditions, such as marine environments or high-temperature settings, promises to elucidate the method’s versatility and widespread applicability in practical scenarios. …”
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Unveiling sentiments of the cullen commission: Exploring AML compliance and regulation through deep learning techniques by Mark E. Lokanan

“…Further research is needed to enhance the understandability and scalability of DL models when analyzing different AML datasets.…”
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Towards Explainable Graph Embeddings for Gait Assessment Using Per-Cluster Dimensional Weighting by Chris Lochhead, Robert B. Fisher

“…Using these embeddings with a K-means clustering approach, the proposed method also outperforms the state of the art by between 4.53 and 16% in classification accuracy across three datasets with a total of 14 different simulated gait pathologies from minor limping to ataxic gait. …”
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GLClick: Interactive Segmentation Combining Global and Local Features by Jiaying Tang, Hongyuan Wang, Zongyuan Ding, Zihao Xin

“…Convolutional neural networks (CNNs) are the backbone of most modern interactive segmentation algorithms. …”
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Handwritten Text Recognition for Documentary Medieval Manuscripts by Sergio Torres Aguilar, Vincent Jolivet

“…However, several challenges must be addressed, including the scarcity of relevant training corpora, the consequential variability introduced by different scribal hands and writing scripts, and the complexity of page layouts. …”
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Deep learning for quantitative dynamic fragmentation analysis by Erwin Cazares, Brian E. Schuster

“…We have developed an image-based convolutional neural network that is applicable for quantitative time-resolved measurements of the fragmentation behavior of opaque brittle materials using ultra-high speed optical imaging. …”
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Multiscale Mask R-CNN–Based Lung Tumor Detection Using PET Imaging by Rui Zhang PhD, Chao Cheng PhD, Xuehua Zhao PhD, Xuechen Li PhD

“…These 3 models were generated by fine-tuning the Mask R-CNN using certain training data that consisted of images from 3 different scales. Each of the training data set included 594 slices with lung tumor. …”
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Research on bearing fault diagnosis based on a multimodal method by Hao Chen, Shengjie Li, Xi Lu, Qiong Zhang, Jixining Zhu, Jiaxin Lu

“…Specifically, the method first employs continuous wavelet transform to generate time-frequency images, capturing local and global features of the signal at different scales. Contrast enhancement techniques are then used to improve the visual quality of these images. …”
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Fusing multiplex heterogeneous networks using graph attention-aware fusion networks by Ziynet Nesibe Kesimoglu, Serdar Bozdag

“…To demonstrate GRAF’s generalizability, we applied it to four datasets from different domains and observed that GRAF outperformed or was on par with the baselines and state-of-the-art (SOTA) methods. …”
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Computer Vision-Based Concrete Crack Identification Using MobileNetV2 Neural Network and Adaptive Thresholding by Li Hui, Ahmed Ibrahim, Riyadh Hindi

“…Concrete is widely used in different types of buildings and bridges; however, one of the major issues for concrete structures is crack formation and propagation during its service life. …”
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CRxK dataset: a multi-view surveillance video dataset for re-enacted crimes in Korea by Chaehee An, Minyoung Lee, Eunil Park

“…CRxK dataset includes a collection of crime re-enacted videos and images categorized into 13 different categories, encompassing a set of offenses such as assault, intoxication, swoon, and more. …”
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The Application of a Marine Weather Data Reconstruction Model Based on Deep Super-Resolution in Ship Route Optimization by Shangfu Li, Junfu Yuan, Zhizheng Wu

“…In addition, the attention mechanism is integrated into the model to dynamically adjust the weights of different weather features, which further enhances the attention to key features. …”
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Deep attributes and decisions fusion for no-reference video quality analysis by Adil Baig

“…Furthermore, the findings show that combining the decisions of different deep networks can greatly improve NR-VQA.…”
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CyclicAugment: Optimized Medical Image Analysis via Adaptive Augmentation Intensity by Min-Jun Kim, Jung-Woo Chae, Hyun-Chong Cho

“…We validated CyclicAugment across six different medical imaging datasets and multiple deep learning architectures, including convolutional neural networks, vision transformers, and multilayer perceptrons. …”
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