Objective Classification of Sea Surface Temperature Evolution diversity of ENSO Cycle by Jiaxi LIU, Zhiwei ZHU, Rui LU, Juan LI

Get full text

Improvement of Multiclass Classification of Pavement Objects Using Intensity and Range Images by Elham Eslami, Hae-Bum Yun

“…Motivated by the need for an improved pavement objects classification, we present Dual Attention Convolutional Neural Network (DACNN) to improve the performance of multiclass classification using intensity and range images collected with 3D laser imaging devices. …”
Get full text

LLMs in Education: Evaluation GPT and BERT Models in Student Comment Classification by Anabel Pilicita, Enrique Barra

“…In this sense, the recent revolution in artificial intelligence, marked by the implementation of powerful large language models (LLMs), may contribute to the classification of student comments. This study compared the effectiveness of a supervised learning approach using five different LLMs: bert-base-uncased, roberta-base, gpt-4o-mini-2024-07-18, gpt-3.5-turbo-0125, and gpt-neo-125m. …”
Get full text

Early Detection and Classification of Diabetic Retinopathy: A Deep Learning Approach by Mustafa Youldash, Atta Rahman, Manar Alsayed, Abrar Sebiany, Joury Alzayat, Noor Aljishi, Ghaida Alshammari, Mona Alqahtani

“…In this experiment, EfficientNetB3 achieved 98.2% accuracy in binary classification and EfficientNetV2B1 achieved 84.4% accuracy in multi-classification, respectively. …”
Get full text

Slit-skin smear for the classification of leprosy; are we wasting time and resource? by Wondmagegn Demsiss, Saskia van Henten, Kudakwashe Collin Takarinda, Edward Mberu Kamau, Seid Getahun Abdela

“…However, the added value of performing SSS for the classification of leprosy on top of clinical classification is unclear. …”
Get full text

Sleep stages classification based on feature extraction from music of brain by Hamidreza Jalali, Majid Pouladian, Ali Motie Nasrabadi, Azin Movahed

“…The overall percentage of correct classification for 6 sleep stages are 88.13 %, 84.3 % and 86.1 % for those databases, respectively. …”
Get full text

Deep learning-based classification of speech disorder in stroke and hearing impairment. by Joo Kyung Park, Sae Byeol Mun, Young Jae Kim, Kwang Gi Kim

“…To achieve effective classification, we employed the ResNet-18, Inception V3, and SEResNeXt-18 models for feature extraction and training processes.…”
Get full text

Usefulness of a new semiological classification for characterizing psychogenic nonepileptic seizures by Bárbara Ingrid ROSSO, Juan Carlos AVALOS, Ana Gabriela BESOCKE, Maria del Carmen GARCÍA

“…Analysis on demographic and clinical data and classification of PNESs according to the Magaudda classification were performed. …”
Get full text

Detection and classification of Shiitake mushroom fruiting bodies based on Mamba YOLO by Kangkang Qi, Zhen Yang, Yangyang Fan, Hualu Song, Zhichao Liang, Shuai Wang, Fengyun Wang

“…Experiments conducted on a self-constructed shiitake mushroom dataset demonstrate that mamba-YOLO achieves precision (P), recall (R), mean average precision calculated at an IoU threshold of 50% (mAP@0.5), and average precision computed over IoU thresholds ranging from 50% to 95% in increments of 5% (mAP@0.5–0.95) of 98.89%, 98.79%, 97.86%, and 89.97%. The classification accuracies for various categories—mushroom stick, plane-surface immature, plane-surface mature, cracked-surface immature, cracked-surface mature, deformed mature, and deformed immature shiitake mushrooms—are 98.1%, 98.3%, 98.2%, 98.8%, 98.5%, 96.2%, and 96.9%. …”
Get full text

A deep learning model for classification of chondroid tumors on CT images by Felix G. Gassert, Daniel Lang, Nina Hesse, Hans Roland Dürr, Alexander Klein, Luca Kohll, Florian Hinterwimmer, Johanna Luitjens, Stefan Weissinger, Jan C. Peeken, Carolin Mogler, Carolin Knebel, Stefan Bartzsch, Florian T. Gassert, Alexandra S. Gersing

Get full text

Stable isotopes as a predictor for organic or conventional classification of berries and vegetables. by Xia Zhu-Barker, Michael Liou, Diana Zapata, Jingyi Huang, William R Horwath

Get full text

An Objective Classification Scheme for Solar-System Bodies Based on Surface Gravity by Dimitris M. Christodoulou, Silas G. T. Laycock, Demosthenes Kazanas

“…Surface gravity <i>g</i> is the property that single-handedly differentiates (a) planets from all other objects (and it leaves no room for questioning the demotion of Pluto), and (b) the six largest (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>g</mi><mo>></mo><mn>1</mn></mrow></semantics></math></inline-formula> m <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi mathvariant="normal">s</mi><mrow><mo>−</mo><mn>2</mn></mrow></msup></semantics></math></inline-formula>) of the large satellites from dwarf planets. …”
Get full text

PROGNOSTIC ROLE OF INFLAMMATORY INDICES IN RISK CLASSIFICATION OF PATIENTS WITH COVID-19 by Maide Hacer Alagöz, Ayşe Enise Göker, Evin Ademoğlu

Get full text

Automatic Detection and Unsupervised Clustering-Based Classification of Cetacean Vocal Signals by Yinian Liang, Yan Wang, Fangjiong Chen, Hua Yu, Fei Ji, Yankun Chen

“…We process 194 audio files in a total of 25.3 h of vocal signal from two marine mammal public databases. …”
Get full text

Clinicopathologic classification of diabetic nephropathy and expression of Ang-2 in renal tissues by WEIZhi-min, MARui-xia, LIU Li-qiu

“…Objective To investigate the clinical value of new pathological classification of diabetic nephropathy(DN) by published Research Committee of the Renal Pathology Society in 2010,and explore the expression and signification of angiopoietin-2(Ang-2) in renal tissues.Methods Renal biopsy was performed on 57 patients with impaired renal function.The tissues were split to be stained by HE,PAS,Masson and PASM for light microscope and stained by IgA,IgG,IgM and C3 for immunofluorescence microscope,and for electron microscope also.All cases were re-classified according to the new pathological classification for DN,and the relationship between the different types of DN and the tubulointerstitial injury was observed.The Ang-2 expression in the renal tissues was detected by immunohistochemistry.Results Before the 2010,19 patients were diagnosed as having DN.After re-analysis according to the new pathological classification,the patients diagnosed with DN were increased to 22,while 32 patients were diagnosed as DN after 2010.In these 54 DN patients,2 cases were classified as type Ⅰ,5 as type Ⅱ a,5 as type Ⅱ b,37 as type Ⅲ and 5 as type Ⅳ.Twenty patients had mild interstitial injury,25 had midrange interstitial injury,and 9 had severe interstitial injury.For all DN research subjects,Ang-2 was detectable to varying degrees in capillaries clump of glomeruli and endothelial cells of blood vessels.The Ang-2 staining was observed in the very early stage of DN.Conclusions The new pathological classification of DN can decrease the misdiagnosis rate and attract more attention to interstitial damage and vessel damage in DN.And for diabetic mellitus patients,Ang-2 detected by renal biopsy could be used for contributing to the early diagnosis and would be beneficial for patients’ individual treatment.…”
Get full text

Symmetry Classification of First Integrals for Scalar Linearizable Second-Order ODEs by K. S. Mahomed, E. Momoniat

“…Secondly, a complete classification of point symmetries of first integrals of such linear ODEs is studied. …”
Get full text

Improving the Accuracy of Batik Classification using Deep Convolutional Auto Encoder by Muhammad Faqih Dzulqarnain, Abdul Fadlil, Imam Riadi

“…Experimental results demonstrate that the incorporation of the autoencoder significantly improved the classification accuracy, achieving 99% accuracy on the testing data and loss value of 3.4%. …”
Get full text

Intelligent Storage Data Classification System Based on the BP Neural Network by Minghui Li

“…In order to solve the problem of multifeature recognition and classification of many kinds of pests, this study puts forward a method of pest feature classification using the BP neural network. …”
Get full text

Multi-Class Classification of Pulmonary Diseases Using Computer Tomography Images by F. Smilianets, О. Finogenov

“…The objective of this study is to examine the behavior of an existing neural network, originally constructed for binary classification, within the context of multi-class classification. …”
Get full text

The Effect of Processing Techniques on the Classification Accuracy of Brain-Computer Interface Systems by András Adolf, Csaba Márton Köllőd, Gergely Márton, Ward Fadel, István Ulbert

“…However, many factors in the processing pipeline can influence classification performance. The objective of this study is to assess the effects of different processing steps on classification accuracy in EEG-based BCI systems. …”
Get full text