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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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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Application of BERT-GCN Model Based on Strong Link Relation Graph in Water Use Enterprise Classification by Junhong Xiang, Baoxian Zheng, Chenkai Cai, Shuiping Yao, Shang Gao

“…Due to the poor quality of current water consumption data and the frequent absence of industry information, accurately calculating the water consumption for different industries is difficult. Therefore, we propose a BERT-GCN model based on a strong link graph for classification within the water industry. …”
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Using spectral imaging for the analysis of abnormalities for colorectal cancer: When is it helpful? by Ruqayya Awan, Somaya Al-Maadeed, Rafif Al-Saady

“…We performed comprehensive analysis using individual bands and different subsets of bands to determine the effectiveness of spectral information for determining the anomaly in colorectal images. …”
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Multifunctional cells based neural architecture search for plant images classification by Lin Huang, Xi Qin, Tiejun Yang

“…Subsequently, an MFC-oriented search strategy is adopted: different shallow blocks from pre-trained models such as MobileNet V3 are searched to construct transfer cell. …”
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Optimizing rainfall-triggered landslide thresholds for daily landslide hazard warning in the Three Gorges Reservoir area by B. Peng, X. Wu

“…Additionally, an innovative application of a three-dimensional convolutional neural network (CNN-3D) model is introduced to enhance the accuracy of landslide susceptibility predictions. …”
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Unsupervised anomaly detection of permanent-magnet offshore wind generators through electrical and electromagnetic measurements by A. Dibaj, M. Valavi, A. R. Nejad

“…Signals analyzed include three-phase currents, induced shaft voltage, electromagnetic torque, and magnetic flux (air gap and stray) from different directions and positions. The performance of CAE models is compared across time and frequency domains. …”
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Post-disaster flooded region segmentation using DeepLabv3+ and unmanned aerial system imagery by Akila Agnes Sundaresan, Appadurai Arun Solomon

“…To evaluate its performance, the study experiments with various backbone architectures, including ResNet-18, ResNet-50, MobileNetV2, and Xception, under different configurations of downsampling rates (8 and 16) and atrous rates (8, 12, and 16). …”
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Innovative data augmentation strategy for deep learning on biological datasets with limited gene representations focused on chloroplast genomes by Mohammad Ali Abbasi-Vineh, Shirin Rouzbahani, Kaveh Kavousi, Masoumeh Emadpour

“…The current augmentation process is highly adaptable, providing flexibility across different types of biological data repositories. Furthermore, a complementary k-mer-based data augmentation strategy was introduced for unlabeled datasets, enhancing unsupervised analysis. …”
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Research on multi-branch residual connection spectrum image classification based on attention mechanism by Zhong Xiaohui, Dong Sheng, Zhang Yiyi, Lu Wei, Jiang Lincen

“…Currently, the extensive use of convolutional neural networks for spectral image classification can extract signal features in the spectrogram, but the redundancy of noisy data generated by a large number of bands of the spectrum affects the feature information at different levels of the image. …”
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