Self-Localization of Guide Robots Through Image Classification by Muhammad S. Alam, Farhan B. Mohamed, AKM B. Hossain

“…A deep learning system, such as a convolutional neural network, trains the self-localization system as an image classification problem.  …”
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Deep-Learning-Based Solar Flare Prediction Model: The Influence of the Magnetic Field Height by Lei Hu, Zhongqin Chen, Long Xu, Xin Huang

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Detection of single and dual pulmonary diseases using an optimized vision transformer by Almughamisi Naif, Abosamra Gibrael, Albar Adnan, Saleh Mostafa

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Fault diagnosis in photovoltaic arrays: A robust and efficient approach using feature engineering and 1D-CNN by Yousif Mahmoud Ali, Lei Ding

“…The proposed 1D-CNN model consists of two convolutional layers, a single max-pooling layer for feature extraction, two fully connected layers, and a softmax layer for fault classification. …”
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Feasibility study of AI-assisted multi-parameter MRI diagnosis of prostate cancer by Yibo Xu, Rongjiang Wang, Zhihai Fang, Jianer Tang

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Deep Learning Algorithm Analysis of Potato Disease Classification for System on Chip Implementation by John Adebisi, Sesham Srinu, Varqa Mitonga

“…Early detection is crucial, prompting the exploration of Convolutional Neural Networks (CNNs) for their disease classification capabilities. …”
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GAPNet: Single and multiplant leaf disease classification method based on simplified SqueezeNet for grape, apple and potato plants by Özge Nur Özaras, Asuman Günay Yılmaz

“…Therefore, agriculture is one of the most important issues in nations. Agriculture also plays a major role in the economic development of countries by increasing economic income. …”
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Mask-SL RCNN: Feature-Enhanced 3D Object Detection Network for Point Clouds by Yuanhong Zhong, Guangxia Yang, Dihang Deng, Panliang Tang, Fan Ren

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A metaheuristic optimization-based approach for accurate prediction and classification of knee osteoarthritis by Amal G. Diab, El-Sayed M. El-Kenawy, Nihal F. F. Areed, Hanan M. Amer, Mervat El-Seddek

“…To address the constraints of this method, several deep learning techniques, particularly the deep convolutional neural networks (CNNs), were applied to increase the efficiency of the proposed workflow. …”
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Breaking Barriers in Thyroid Cytopathology: Harnessing Deep Learning for Accurate Diagnosis by Seo Young Oh, Yong Moon Lee, Dong Joo Kang, Hyeong Ju Kwon, Sabyasachi Chakraborty, Jae Hyun Park

“…The first framework is a patch-level classifier referred as “TCS-CNN”, based on a convolutional neural network (CNN) architecture, to predict thyroid cancer based on the Bethesda System (TBS) category. …”
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Automated approaches for the early stage distinguishing of Palmer amaranth from waterhemp by Akhil Venkataraju, Dharanidharan Arumugam, Ravi Kiran, Thomas Peters

“…Palmer amaranth and waterhemp are two invasive pigweed species, which have become most troublesome to crops, especially corn and soybean. …”
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Electromyography-Based Gesture Recognition With Explainable AI (XAI): Hierarchical Feature Extraction for Enhanced Spatial-Temporal Dynamics by Jungpil Shin, Abu Saleh Musa Miah, Sota Konnai, Shu Hoshitaka, Pankoo Kim

“…The third branch, combining a Temporal Convolutional Network (TCN) and Bidirectional LSTM (BiLSTM), captures bidirectional temporal relationships and time-varying patterns. …”
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A Machine Learning Free Energy Functional for the 1D Reference Interaction Site Model: Towards Prediction of Solvation Free Energy for All Solvent Systems by Jonathan G. M. Conn, Abdullah Ahmad, David S. Palmer

“…In this work, we show that a single machine learning free energy functional for RISM can accurately model solvation thermodynamics in multiple solvents. A convolutional neural network is trained on solvation free energy density functions calculated by RISM for small organic molecules in approximately 100 different solvent systems. …”
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PermQRDroid: Android malware detection with novel attention layered mini-ResNet architecture over effective permission information image by Kazım Kılıç, İbrahim Alper Doğru, Sinan Toklu

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A Predictive Method for Unplanned Postoperative Readmission Risk Based on Heterogeneous Data by Kai YU, Xiaofeng DONG, Zhenming YUAN, Zhaojian CUI, Weibin LUO

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Image Classification Model Based on Contrastive Learning With Dynamic Adaptive Loss by Quandeng Gou, Jingxuan Zhou, Zi Li, Fangrui Zhang, Yuheng Ren

“…As one of the core tasks in vision recognition, image classification is widely used in various scenarios. Most existing mainstream image classification models use the Convolutional Neural Network (CNN), the Transformer, or a combination of both as the backbone. …”
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Towards Parkinson’s Disease Detection Through Analysis of Everyday Handwriting by Jeferson David Gallo-Aristizabal, Daniel Escobar-Grisales, Cristian David Ríos-Urrego, Jesús Francisco Vargas-Bonilla, Adolfo M. García, Juan Rafael Orozco-Arroyave

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Application of deep learning model based on unenhanced chest CT for opportunistic screening of osteoporosis: a multicenter retrospective cohort study by Chengbin Huang, Dengying Wu, Bingzhang Wang, Chenxuan Hong, Jiasen Hu, Zijian Yan, Jianpeng Chen, Yaping Jin, Yingze Zhang

“…This study aimed to establish and validate a convolutional neural network (CNN) model based on unenhanced chest computed tomography (CT) images of the vertebral body and skeletal muscle for opportunistic screening in patients with osteoporosis. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…Objective Combining an inertial navigation system (INS) and a global positioning system (GPS) in stable conditions of GPS satellite signals offers the most accurate altitude indication, termed inertial satellite composite altitude. …”
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A Forecast-Refinement Neural Network Based on DyConvGRU and U-Net for Radar Echo Extrapolation by Jinliang Yao, Feifan Xu, Zheng Qian, Zhipeng Cai

“…To improve the model’s ability to predict high reflectivities, dynamic convolution, and the forecast-refinement architecture are applied. …”
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