Interpreting the CTCF-mediated sequence grammar of genome folding with AkitaV2. by Paulina N Smaruj, Fahad Kamulegeya, David R Kelley, Geoffrey Fudenberg

“…Here, we update and utilize Akita, a convolutional neural network model, to extract the sequence preferences and grammar of CTCF contributing to genome folding. …”
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Speech Databases, Speech Features, and Classifiers in Speech Emotion Recognition: A Review by G. H. Mohmad Dar, Radhakrishnan Delhibabu

“…It also analyzes the efficacy of different speech features and classifiers in handling challenges such as data imbalance, limited data availability, and cross-lingual variations. …”
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Few-Shot Learning in Wi-Fi-Based Indoor Positioning by Feng Xie, Soi Hoi Lam, Ming Xie, Cheng Wang

“…This paper explores the use of few-shot learning in Wi-Fi-based indoor positioning, utilizing convolutional neural networks (CNNs) combined with meta-learning techniques to enhance the accuracy and efficiency of positioning systems. …”
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Legal Perspectives for Explainable Artificial Intelligence in Medicine - Quo Vadis? by Cătălin-Mihai PESECAN, Lăcrămioara STOICU-TIVADAR

“…Grad-CAM will generate heatmaps based on the gradient from the last layer (because it contains the most information) of a convolutional neural network. Explainable Artificial Intelligence methods come in multiple flavors and options and can offer different perspectives. …”
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DANC-Net: Dual-Attention and Negative Constraint Network for Point Cloud Classification by Hang Sun, Yuanyue Zhang, Jinmei Shi, Shuifa Sun, Guanqun Sheng, Yirong Wu

“…Convolutional neural networks, as a branch of deep neural networks, have been widely used in multidimensional signal processing, especially in point cloud signal processing. …”
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Salient object detection dataset with adversarial attacks for genetic programming and neural networksMendeley Data by Matthieu Olague, Gustavo Olague, Roberto Pineda, Gerardo Ibarra-Vazquez

“…Salient object detection is a research area where deep convolutional neural networks have proven effective but whose trustworthiness represents a significant issue requiring analysis and solutions to hackers' attacks. …”
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Detection of the Pin Defects of Power Transmission Lines Based on Improved TPH-MobileNetv3 by Mengxuan Li, Jingshan Han, Zhi Yang, Bin Zhao, Peng Liu

“…A feature fusion structure with layers of self-attention and a convolutional block attention module (CBAM) is added to the neck network, and a transformer prediction head are added to the head network so that different scale characteristics can be fused and focused from space and channels to strengthen the detection of small targets. …”
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A Hybrid Approach for Color Face Recognition Based on Image Quality Using Multiple Color Spaces by Mahdi Hosseinzadeh, Mohammad Mehdi Pazouki, Önsen Toygar

“…Additionally, the proposed system is designed to serve as a secure anti-spoofing mechanism, tested against different attack scenarios, including print attacks, mobile attacks, and high-definition attacks. …”
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Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images by Avigyan Roy, Priyam Saha, Nandita Gautam, Friedhelm Schwenker, Ram Sarkar

“…They are an essential tool in the study and understanding of diseases, aiding in research, education, and patient care. Convolutional neural network based pretrained deep learning models can be used successfully to detect lung cancer. …”
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FROM PIXELS TO DIAGNOSIS: A DEEP LEARNING FRAMEWORK FOR HISTOPATHOLOGICAL IMAGE ANALYSIS IN CANINE TESTICULAR PATHOLOGY

“…We propose an artificial intelligence-based computational pathology approach to automate the discrimination of different testicular developmental, inflammatory or degenerative pathologies and the main testicular neoplasms (Seminoma, Sertolioma, Leydigoma). …”
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Quality Judgment of 3D Face Point Cloud Based on Feature Fusion by Gong Gao, Hong Liu, Hongyu Yang

“…Secondly, Dynamic Graph Convolutional Neural Network (DGCNN) was trained for point cloud learning and ShuffleNet was trained for image learning. …”
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UNIFIED MULTIMODAL BIOMETRICS FUSION USING DEEP LEARNING FOR SECURING IOT by Prabhjot Kaur, Chander Kaur

“…Our proposed approach employs “Convolutional Neural Network (CNN)” architectures, notable for their efficacy in computer vision tasks, to extract potent discriminative features from the input images. …”
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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

“…To enhance detection sensitivity, a deep neural model integrating generative and convolutional networks was used to enable quantitative biomarker diagnosis from smartphone photos. …”
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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

“…This study presents a combination of two parallel Convolutional Neural Networks (CNNs) and an ensemble learning method for classifying AD stages using Magnetic Resonance Imaging (MRI) data. …”
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Utilizing EfficientNet for sheep breed identification in low-resolution images by Galib Muhammad Shahriar Himel, Md. Masudul Islam, Mijanur Rahaman

“…To address this objective, we propose employing a convolutional neural network (CNN) model capable of rapidly and accurately identifying sheep breeds from low-resolution images. …”
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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

“…The method integrates a convolutional neural network (CNN) and a multilayer perceptron (MLP) model to monitor stiffness degradation in bridge spans over time, representing a significant step forward in SHM techniques. …”
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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

“…To address this applicational barrier, an end-to-end pipeline is introduced here for creating graph feature embeddings, generated using a bespoke Spatio-temporal Graph Convolutional Network and per-joint Principal Component Analysis. …”
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