Rapid Disaster Data Dissemination and Vulnerability Assessment through Synthesis of a Web-Based Extreme Event Viewer and Deep Learning by P. Shane Crawford, Mohammad A. Al-Zarrad, Andrew J. Graettinger, Alexander M. Hainen, Edward Back, Lawrence Powell

“…Approximately 1,950 buildings were passively documented with vehicle-mounted 360° video. Extracted building images were used to train a deep learning neural network to predict whether a building was elevated or nonelevated. …”
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FL-QNNs: Memory Efficient and Privacy Preserving Framework for Peripheral Blood Cell Classification by Meenakshi Aggarwal, Vikas Khullar, Nitin Goyal, Bhavani Sankar Panda, Hardik Doshi, Nafeesh Ahmad, Vivek Bhardwaj, Gaurav Sharma

“…The data set include the total 17,092 images of eight classes. …”
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The Relationship Between Age and the Propofol Dose for Anesthesia Induction: A Single-Center Retrospective Study Utilizing Neural Network Model Simulation by Kazuki Nishimura, Kenji Hirata, Fujita Noriaki, Akira Watabe, Yuji Morimoto

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Automatic melanoma and non-melanoma skin cancer diagnosis using advanced adaptive fine-tuned convolution neural networks by Muhammad Amir Khan, Tehseen Mazhar, Muhammad Danish Ali, Umar Farooq Khattak, Tariq Shahzad, Mamoon M. Saeed, Habib Hamam

“…In this research, we advise an intelligent computer-aided system for automatic skin cancer diagnosis using a two-stage transfer learning approach and Pre-trained Convolutional Neural Networks (CNNs). CNNs are well-suited for learning hierarchical features from images. …”
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Integration of multi-temporal SAR data and robust machine learning models for improvement of flood susceptibility assessment in the southwest coast of India by Pankaj Prasad, Sourav Mandal, Sahil Sandeep Naik, Victor Joseph Loveson, Simanku Borah, Priyankar Chandra, Karthik Sudheer

“…Therefore, the main aim of the present study is to prepare a flood susceptible map of the southwest coastal region of India using synthetic-aperture radar (SAR) data and robust machine learning algorithms. Accurate flood and non-flood locations have been identified from the multi-temporal Sentinel-1 images. …”
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A Voxelized Transformer-Based Neural Network for 3D Reconstruction From Multi-Energy SEM Backscattered Electrons by Caizhi Zheng, Ronghan Hong, Hao-Jie Hu, Qing Huo Liu

“…Three-dimensional (3D) data analysis, especially 3D reconstruction, is critical within integrated circuits for quality control and inspection. …”
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Transcranial pulse stimulation (TPS) improves depression in AD patients on state‐of‐the‐art treatment by Eva Matt, Gregor Dörl, Roland Beisteiner

“…FC analysis showed a normalization of the FC between the salience network (right anterior insula) and the ventromedial network (left frontal orbital cortex). …”
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Keypoints-Based Multi-Cue Feature Fusion Network (MF-Net) for Action Recognition of ADHD Children in TOVA Assessment by Wanyu Tang, Chao Shi, Yuanyuan Li, Zhonglan Tang, Gang Yang, Jing Zhang, Ling He

“…For facial keypoints, we transform data into images and employ MobileVitv2 for transfer learning to capture facial and head movement features. …”
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A neural network model enables worm tracking in challenging conditions and increases signal-to-noise ratio in phenotypic screens. by Weheliye H Weheliye, Javier Rodriguez, Luigi Feriani, Avelino Javer, Virginie Uhlmann, André E X Brown

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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…If the divergence persists, the ESP32 node activates a camera to capture an image of the panel and sends it to the Google Sheet via a connection for further analysis and fault correction. …”
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A Backdoor Attack Against LSTM-Based Text Classification Systems by Jiazhu Dai, Chuanshuai Chen, Yufeng Li

“…We consider the backdoor attack in black-box setting, where the adversary has no knowledge of model structures or training algorithms except for a small amount of training data. We verify the attack through sentiment analysis experiment on the dataset of IMDB movie reviews. …”
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Comparative Analysis of Facial Expression Recognition Methods by Denys - Florin COT

“… This paper aimed to investigate human emotion recognition through the analysis of facial expressions, using both classical machine learning methods and advanced techniques based on deep neural networks. …”
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Enhancing Thyroid Nodule Assessment With UTV-ST Swin Kansformer: A Multimodal Approach to Predict Invasiveness by Yufang Zhao, Yue Li, Yanjing Zhang, Xiaohui Yan, Guolin Yin, Liping Liu

“…By analyzing ultrasound video features using the Video Swin Transformer and clinical data using a text analysis module based on the KAN network, and then fusing these features, the model achieves a classification accuracy of 82.1% and an average AUC of 94.2%. …”
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Time-varying spectral power of resting-state fMRI networks reveal cross-frequency dependence in dynamic connectivity. by Maziar Yaesoubi, Robyn L Miller, Vince D Calhoun

“…This limits the range of detectable frequency bands in fMRI and consequently there has been no evidence of cross-frequency dependence in fMRI data. In the present work we uncover recurring patterns of spectral power in network timecourses which provides new insight on the actual nature of frequency variation in fMRI network activations. …”
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Synthesizing field plot and airborne remote sensing data to enhance national forest inventory mapping in the boreal forest of Interior Alaska by Pratima Khatri-Chhetri, Hans-Erik Andersen, Bruce Cook, Sean M. Hendryx, Liz van Wagtendonk, Van R. Kane

“…To achieve this goal, we compared the performance of two advanced modeling approaches, the convolutional neural network (CNN) and the XGBoost model. Our datasets included field and high-resolution topographic metrics including elevation, slope, aspect, and solar radiation and canopy height derived from lidar (1 m) and 44 vegetation indices derived from high-resolution (1 m) visible to near infrared (VNIR) hyperspectral data collected by NASA Goddard's Lidar, Hyperspectral and Thermal Imager (G-LiHT) sensor. …”
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Machine Learning for Human Activity Recognition: State-of-the-Art Techniques and Emerging Trends by Md Amran Hossen, Pg Emeroylariffion Abas

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Design and implementation of quantum hippo inspired convolutional neural networks using parametric quantum circuits for an efficient lung cancer classification by S. Radhika, G. Sharada

“…The proposed learning framework consists of four components namely Data collection & Data pre-processing, Classical Hippo Optimized Convolutional Neural networks, and Quantum based model using parametric quantum circuits (PQC), Evaluation and Analysis. …”
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Improving the Universal Performance of Land Cover Semantic Segmentation Through Training Data Refinement and Multi-Dataset Fusion via Redundant Models by Jae Young Chang, Kwan-Young Oh, Kwang-Jae Lee

“…In this study, we propose a method to mitigate these inconsistencies by utilizing redundant models and verify the improvement using a public dataset based on Google Earth images. Redundant models share the same network architecture and hyperparameters but are trained with different combinations of training and validation data on the same dataset. …”
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Swarm learning network for privacy-preserving and collaborative deep learning assisted diagnosis of fracture: a multi-center diagnostic study by Yi Xie, Yi Xie, Xinmeng Wang, Huiwen Yang, Huiwen Yang, Jiayao Zhang, Honglin Wang, Zineng Yan, Jiaming Yang, Zhiyuan Yan, Zhiwei Hao, Pengran Liu, Yijie Kuang, Zhewei Ye, Zhewei Ye

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An Automated Semantic Segmentation Methodology for Infrared Thermography Analysis of the Human Hand by Melchior Arnal, Cyprien Bourrilhon, Vincent Beauchamps, Fabien Sauvet, Hassan Zahouani, Coralie Thieulin

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