Post-disaster flooded region segmentation using DeepLabv3+ and unmanned aerial system imagery by Akila Agnes Sundaresan, Appadurai Arun Solomon

“…ResNet-50 proves to be the most effective backbone, achieving the optimal balance between segmentation accuracy and computational efficiency. …”
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Distinguish the Value of the Benign Nevus and Melanomas Using Machine Learning: A Meta-Analysis and Systematic Review by Suli Li, Yihang Chu, Ying Wang, Yantong Wang, Shipeng Hu, Xiangye Wu, Xinwei Qi

“…Background. Melanomas, the most common human malignancy, are primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy, and histopathological examination. …”
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Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids by Yanfei Li, Juejing Liu, Xiaodong Zhao, Wenjun Liu, Tong Geng, Ang Li, Xin Zhang

“…Most significantly, MTL models tuned to analyze raw and unmasked XRD patterns achieve close performance to models analyzing preprocessed data, with minimal accuracy differences. …”
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SMART HYBRID MODELS FOR IMPROVED BREAST CANCER DETECTION by Nageswara Rao Gali, Panduranga Vital Terlapu, Yasaswini Mandavakuriti, Sai Manoj Somu, Madhavi Varanasi, Vijay Telugu, Maheswara Rao V V R

“…Breast cancer (BC) ranks the second most prevalent cancer among women globally and is the leading cause of female mortality. …”
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A Novel Dual-Stream Attention-Based Hybrid Network for Solar Power Forecasting by Rafiq Asghar, Michele Quercio, Lorenzo Sabino, Assia Mahrouch, Francesco Riganti Fulginei

“…This research introduces a novel dual-steam hybrid model that uses Bidirectional Long-Short Term Memory (BiLSTM) and Convolutional Neural Networks (CNN) to predict PV power production. …”
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An advanced CNN-attention model with IFTTA optimization for prediction air consumption of relay nozzles by Shen Min, Shao Ning, Cao Yongbo, Xiong Xiaoshuang, Yang Xuezheng, Wang Zhen, Yu Lianqing

“…An in-depth analysis of predicted data reveals that the outlet diameter is the most sensitive factor affecting the airflow rate, followed by inlet diameters and cone angle of the relay nozzle. …”
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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

“…The performance metrics showed similar results for the first two approaches, but FixCaps was the most proficient, with accuracy, precision, recall, and F‐score of 93.83%, 95.41%, 88.63%, and 90.93% respectively. …”
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A Lightweight Direction-Aware Network for Vehicle Detection by Luxia Yang, Yilin Hou, Hongrui Zhang, Chuanghui Zhang

“…Vehicle detection algorithms, which are essential to intelligent traffic management and control systems, have attracted growing attention. However, most high-precision vehicle detection algorithms suffer from high computational effort and slow detection speeds, resulting in the challenging task of deploying these algorithms on mobile devices. …”
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Deep Learning for Connectivity Identification in Random Subsurface Flows: A Methodological Workflow for Early Solute Arrival Time Quantification by A. Manzoni, F. P. J. deBarros, G. M. Porta, M. Riva, A. Guadagnini

“…Our methodology is based on a two‐stage approach that combines Convolutional Neural Networks (CNN) and Multi‐Layer Perceptron (MLP) techniques. …”
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Building Damage Detection Using Deep Learning Architecture with Satellite Images: The Case of the 6 February 2023 Kahramanmaraş Earthquake by Zeynep Aygün, Merve Kocaman, Salih Aydemir, Berkant Konakoğlu

“…The Kahramanmaraş earthquake on February 6, 2023, was one of the most devastating in recent years, causing extensive damage and loss. …”
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CD-CTFM: A Lightweight CNN-Transformer Network for Remote Sensing Cloud Detection Fusing Multiscale Features by Wenxuan Ge, Xubing Yang, Rui Jiang, Wei Shao, Li Zhang

“…Hence, cloud detection is a necessary preprocessing procedure. However, most existing methods have numerous calculations and parameters. …”
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GCAFlow: Multi-Scale Flow-Based Model with Global Context-Aware Channel Attention for Industrial Anomaly Detection by Lin Liao, Congde Lu, Yujie Gao, Hao Yu, Biao Cai

“…Recent work has largely focused on feature fusion strategies. However, most of the flow-based methods emphasize spatial information while neglecting the critical role of channel-wise features. …”
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Brain-Inspired Architecture for Spiking Neural Networks by Fengzhen Tang, Junhuai Zhang, Chi Zhang, Lianqing Liu

“…Spiking neural networks (SNNs), using action potentials (spikes) to represent and transmit information, are more biologically plausible than traditional artificial neural networks. However, most of the existing SNNs require a separate preprocessing step to convert the real-valued input into spikes that are then input to the network for processing. …”
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Multilevel Feature Gated Fusion Based Spatial and Frequency Domain Attention Network for Joint Classification of Hyperspectral and LiDAR Data by Cuiping Shi, Zhipeng Zhong, Shihang Ding, Yeqi Lei, Liguo Wang, Zhan Jin

“…First, extract multilevel convolutional features from hyperspectral and LiDAR images and adaptively fuse them through a gating mechanism. …”
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Intelligent Fault Diagnosis of Inter-Turn Short Circuit Faults in PMSMs for Agricultural Machinery Based on Data Fusion and Bayesian Optimization by Mingsheng Wang, Wuxuan Lai, Hong Zhang, Yang Liu, Qiang Song

“…Inter-turn short circuit (ITSC) faults are among the most common failures in PMSMs, and early diagnosis of these faults is crucial for enhancing the safety and reliability of motor operation. …”
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Hybrid Darknet53-SVM model with random grid search optimization for enhanced colorectal cancer histological image classification by Pragati Patharia, Prabira Kumar Sethy, K. Lakshmipathi Raju, Anita Khanna, Ashoka Kumar Ratha, Santi Kumari Behera, Aziz Nanthaamornphong

“…Initially, 18 pre-trained Convolutional Neural Networks (CNNs) were evaluated using transfer learning techniques. …”
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Multimodal fusion transformer network for multispectral pedestrian detection in low-light condition by Gong Li, Guoyin Ren, Jingyu Wang, Mobing Zhi, Zhijie Yu, Bo Jiang, Haoliang Guan, Qidan Guo

“…Abstract Multispectral pedestrian detection has attracted significant attention owing to its advantages, such as providing rich information, adapting to various scenes, enhancing features, and diversifying applications. However, most existing fusion methods are based on convolutional neural network (CNN) feature fusion. …”
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Assessment of Bone Aging—A Comparison of Different Methods for Evaluating Bone Tissue by Paweł Kamiński, Aleksander Gali, Rafał Obuchowicz, Michał Strzelecki, Adam Piórkowski, Marcin Kociołek, Elżbieta Pociask, Joanna Kwiecień, Karolina Nurzyńska

“…The use of artificial intelligence in medical data analysis produces comparable outcomes; however, when dealing with a large number of descriptors, selecting the most optimal ones through statistical analysis enables the identification of the best solution quickly.…”
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Local Auxiliary Spatial–Spectral Decoupling Transformer Network for Cross-Scene Hyperspectral Image Classification by Qiusheng Chen, Zhuoqun Fang, Zhaokui Li, Qian Du, Shizhuo Deng, Tong Jia, Dongyue Chen

“…The feature-level domain alignment based on deep learning techniques has greatly improved the performance of unsupervised domain adaptation (UDA) for hyperspectral image (HSI) classification. However, most of these methods leverage convolutional neural networks to capture local features, overlooking the comparable spatial global (SaG) and spectral global (SeG) information shared by both the source and target domains. …”
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Remaining Useful Life Prediction for Pressurized Fluid Pipelines Based on Acoustic Emission Monitoring and an Adaptive Fuzzy Similarity Measure by Duc-Thuan Nguyen, Tuan-Khai Nguyen, Zahoor Ahmad, Jong-Myon Kim

“…Pressurized fluid pipelines are among the most crucial components in industrial settings. Operating under high pressure leads to pipeline susceptibility to cracking, rupture, and significant damage. …”
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