SkinIncept: an ensemble transfer learning-based approach for multiclass skin disease classification using InceptionV3 and InceptionResNetV2 by Md. Hasan Imam Bijoy, Md. Mahbubur Rahman, Abdus Sattar, Aminul Haque, Mohammad Shamsul Arefin, Pranab Kumar Dhar, Tetsuya Shimamura

“…This study addresses this critical issue by developing a robust and accurate system for classifying Bangladesh’s ten most common skin diseases using convolutional neural networks (CNNs)-based transfer learning models. …”
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Impact of lens autofluorescence and opacification on retinal imaging by Frank G Holz, Maximilian Pfau, Monika Fleckenstein, Raffael Liegl, Geena C Rennen, Marc Vaisband, Jan Hasenauer

“…BAF image quality was most vulnerable to an increase in lenticular metrics, while IR (−0.19 (−0.38 to 0.01)) demonstrated the highest resilience.Conclusion The use of CNN-based retinal image quality assessment achieved excellent results. …”
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Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…The proposed approach begins with feature extraction using ResNet50, a deep convolutional neural network known for its robust feature representation capabilities. …”
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Forecasting Indoor Air Quality in Mexico City Using Deep Learning Architectures by Jorge Altamirano-Astorga, J. Octavio Gutierrez-Garcia, Edgar Roman-Rangel

“…However, those systems forecast outdoor air quality while people living in relatively large cities spend most of their time indoors. Hence, this work proposes an indoor air quality forecasting system, which was trained with data from Mexico City, and that is supported by deep learning architectures. …”
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A New and Tested Ionospheric TEC Prediction Method Based on SegED-ConvLSTM by Yuanhang Liu, Yingkui Gong, Hao Zhang, Ziyue Hu, Guang Yang, Hong Yuan

“…We compared our model with traditional image-based models such as convolutional neural networks (CNNs), convolutional long short-term memory networks (ConvLSTMs), a self-attention mechanism-integrated ConvLSTM (SAM-ConvLSTM) model, and one-day predicted ionospheric products (C1PG) provided by the Center for Orbit Determination in Europe (CODE). …”
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Hybrid Reinforcement Learning-Based Collision Avoidance Algorithm for Autonomous Vehicle Clusters by Chubing Guo, Jianshe Wu, Panzheng Luo, Zhigang Wang, Kai Zhang, Ziyi Yang, Zengfa Dou, Kan Song

“…The experimental results show that the proposed algorithm in this study showed a high success rate of collision avoidance and a low average reaction time under most collision avoidance times.…”
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Energy-Efficient on-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing by Flor Ortiz, Nicolas Skatchkovsky, Eva Lagunas, Wallace A. Martins, Geoffrey Eappen, Saed Daoud, Osvaldo Simeone, Bipin Rajendran, Symeon Chatzinotas

“…Most notably, for relevant workloads, Spiking Neural Networks (SNNs) implemented on Loihi 2 yield higher accuracy, while reducing power consumption by more than <inline-formula> <tex-math notation="LaTeX">$100\times $ </tex-math></inline-formula> as compared to the CNN-based reference platform. …”
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Development of Smart Models to Accurately Predict Dynamic Viscosity of CO2-Saturated Polyethylene Glycol by Ayat Hussein Adhab, Morug Salih Mahdi, Bhavesh Kanabar, Anupam Yadav, Ranganathaswamy M K, Rishabh Thakur, Parveen Kumar, Braj Krishna, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…Ultimately, multilayer perceptron artificial neural network model is found to be the most accurate method for predicting CO2-saturated PEG viscosity.…”
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FTIR-Based Microplastic Classification: A Comprehensive Study on Normalization and ML Techniques by Octavio Villegas-Camacho, Iván Francisco-Valencia, Roberto Alejo-Eleuterio, Everardo Efrén Granda-Gutiérrez, Sonia Martínez-Gallegos, Daniel Villanueva-Vásquez

“…The results showed that Z-score normalization significantly improved stability and generalization across most models, with CNN, MLP, and RF achieving near-perfect values in accuracy, precision, recall, and F1-score. …”
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A forestry investigation: Exploring factors behind improved tree species classification using bark images by Gokul Kottilapurath Surendran, Deekshitha, Martin Lukac, Martin Lukac, Jozef Vybostok, Martin Mokros

“…Additionally, the aim is to determine the most effective algorithmic approaches for efficient tree species classification from bark images and to make these methods more accessible to interdisciplinary researchers. …”
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A capsule network framework for flood mapping integrating remote sensing fusion techniques by Pouya Ahmadi, Mohammad Javad Valadan Zoej, Mehdi Mokhtarzade, Nazila Kardan Halvaie, Ebrahim Ghaderpour

“…Flooding is one of the most serious natural hazards worldwide, causing significant and often irreversible damage to economies, infrastructure, and human health in urban areas. …”
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A Multi-Spatial-Scale Ocean Sound Speed Profile Prediction Model Based on a Spatio-Temporal Attention Mechanism by Shuwen Wang, Ziyin Wu, Shuaidong Jia, Dineng Zhao, Jihong Shang, Mingwei Wang, Jieqiong Zhou, Xiaoming Qin

“…Moreover, in terms of ocean sound speed, most of these models predict an ocean sound speed profile (SSP) at a single coordinate position, and only a few predict multi-spatial-scale SSPs. …”
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Exploring vision transformers and XGBoost as deep learning ensembles for transforming carcinoma recognition by Akella Subrahmanya Narasimha Raju, K. Venkatesh, B. Padmaja, CH. N. Santhosh Kumar, Pattabhi Rama Mohan Patnala, Ayodele Lasisi, Saiful Islam, Abdul Razak, Wahaj Ahmad Khan

“…Abstract Early detection of colorectal carcinoma (CRC), one of the most prevalent forms of cancer worldwide, significantly enhances the prognosis of patients. …”
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Artificial intelligence−assisted radiation imaging pathways for distinguishing uterine fibroids and malignant lesions in patients presenting with cancer pain: a literature review by Chengfeng Cai, Wenhui Hu, Haimei Zhou, Xian Zhang, Rongfei Ren, Yilin Liu, Facui Ye

“…Uterine fibroids (leiomyomas) are the most common benign uterine tumours, affecting a significant portion of women, and often present with symptoms similar to malignant tumours, such as leiomyosarcoma or endometrial carcinoma, particularly in patients with cancer-related pelvic pain. …”
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FUSCANet: Enhancing Skin Disease Classification Through Feature Fusion and Spatial-Channel Attention Mechanisms by Qinyang Liu, Xuan Wang, Hongjiu Liu, Xiangzhen Zang, Lei Li, Zhanlin Ji, Ivan Ganchev

“…The obtained experimental results show that FUSCANet outperforms existing models on most evaluation metrics, while maintaining low parameter counts, making it suitable for deployment in resource-constrained environments.…”
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Consistency Regularization for Semi-Supervised Semantic Segmentation of Flood Regions From SAR Images by G. Savitha, S. Girisha, Pundarika Sughosh, Dasharathraj K. Shetty, Jayaraj Mymbilly Balakrishnan, Rahul Paul, Nithesh Naik

“…As one of the most powerful natural catastrophes, floods pose serious risks to people&#x2019;s lives, the integrity of infrastructure, and agricultural landscapes, which increases the toll they take on the economy and society. …”
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Exploration of machine learning approaches for automated crop disease detection by Annu Singla, Ashima Nehra, Kamaldeep Joshi, Ajit Kumar, Narendra Tuteja, Rajeev K. Varshney, Sarvajeet Singh Gill, Ritu Gill

“…This systematic review provides a comprehensive analysis after text mining the most recent literature resources of the last half a decade. …”
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Time-Distributed Vision Transformer Stacked With Transformer for Heart Failure Detection Based on Echocardiography Video by Mgs M. Luthfi Ramadhan, Adyatma W. A. Nugraha Yudha, Muhammad Febrian Rachmadi, Kevin Moses Hanky Jr Tandayu, Lies Dina Liastuti, Wisnu Jatmiko

“…Existing studies have employed artificial intelligence to help with heart failure screening and diagnosis processes based on echocardiography videos. Specifically, most existing studies use a convolutional neural network that only captures the local context of an image hindering it from learning the global context of an image. …”
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Global surface eddy mixing ellipses: spatio-temporal variability and machine learning prediction by Tian Jing, Ru Chen, Chuanyu Liu, Chunhua Qiu, Chunhua Qiu, Cuicui Zhang, Mei Hong

“…Feature importance rankings indicate that eddy velocity magnitude and eddy size are the most significant factors in predicting the major axis and anisotropy. …”
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MWFNet: A multi-level wavelet fusion network for hippocampal subfield segmentation by Xinwei Li, Linjin Wang, Weijian Tao, Hongying Meng, Haiming Li, Jiangtao He, Yue Zhao, Jun Hu, Zhangyong Li

“…Additionally, we developed a Multi-scale Attention Residual Block (MARB) that leverages convolutional kernels of different sizes to facilitate multi-scale feature extraction. …”
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