An Explainable Deep Learning Network for Environmental Microorganism Classification Using Attention-Enhanced Semi-Local Features by R. Karthik, Armaano Ajay, Akshaj Singh Bisht, Jaehyuk Cho, V. E. Sathishkumar

Get full text

Geospatial and multi-criteria decision analysis for sustainable solid waste disposal site selection in Debre Tabor, Ethiopia by Biksegn Mulualem, Tenalem Ayenew, Gashaw Tesfaw, Muralitharan Jothimani, Wuletaw Mulualem

Get full text

LCAT: A Lightweight Color-Aware Transformer With Hierarchical Attention for Leaf Disease Classification in Precision Agriculture by Parkpoom Chaisiriprasert, Khachonkit Chuiad

“…The experimental results show that LCAT outperforms standard Vision Transformer (ViT) models with a similar number of parameters. In particular, LCAT achieves a mean average precision (mAP) of 0.81 and a classification accuracy of 0.75, compared to ViT’s mAP of 0.75 and an accuracy of 0.68, while using significantly fewer floating-point operations (FLOPs), at 3.33G vs. 17.58G. …”
Get full text

Towards precision in IoT-based healthcare systems: a hybrid optimized framework for big data classification by Satheeshkumar Palanisamy, Vigneshwaran Thangaraju, Jeevitha Kandasamy, Ayodeji Olalekan Salau

Get full text

Queuing Pricing with Time-Varying and Step Tolls: A Mathematical Framework for User Classification and Behavioral Analysis by Chen-Hsiu Laih

“…The analysis reveals a structured classification of users into 3<i>n</i> + 2 behavioral groups, with predictable proportions in each category. …”
Get full text

Data-Driven Fault Detection and Diagnosis in Cooling Units Using Sensor-Based Machine Learning Classification by Amilcar Quispe-Astorga, Roger Jesus Coaquira-Castillo, L. Walter Utrilla Mego, Julio Cesar Herrera-Levano, Yesenia Concha-Ramos, Erwin J. Sacoto-Cabrera, Edison Moreno-Cardenas

Get full text

A stochastic optimization method for economic microgrid operation based on "source-load operation" mode classification by ZHOU Hang, MA Lihong, LI Zhongzhong, WANG Haisheng, LI Sifan, ZHANG Changjun, FU Linbei

Get full text

An Enhanced Machine Learning Framework for Type 2 Diabetes Classification Using Imbalanced Data with Missing Values by Kumarmangal Roy, Muneer Ahmad, Kinza Waqar, Kirthanaah Priyaah, Jamel Nebhen, Sultan S Alshamrani, Muhammad Ahsan Raza, Ihsan Ali

Get full text

Multimodal Alzheimer’s disease classification through ensemble deep random vector functional link neural network by Pablo A. Henríquez, Nicolás Araya

Get full text

Machine learning classification and biochemical characteristics in the real-time diagnosis of gastric adenocarcinoma using Raman spectroscopy by Alex Noh, Sabrina Xin Zi Quek, Nuraini Zailani, Juin Shin Wee, Derrick Yong, Byeong Yun Ahn, Khek Yu Ho, Hyunsoo Chung

Get full text

Dual-Stream Contrastive Latent Learning Generative Adversarial Network for Brain Image Synthesis and Tumor Classification by Junaid Zafar, Vincent Koc, Haroon Zafar

“…The generated images undergo adversarial refinement using an ensemble of specialized discriminators, where discriminator 1 (D1) ensures classification consistency with real MRI images, discriminator 2 (D2) produces a probability map of localized variations, and discriminator 3 (D3) preserves structural consistency. …”
Get full text

Artificial intelligence-driven classification method of grapevine major phenological stages using conventional RGB imaging by Ruben Íñiguez, Fikile Wolela, María Ignacia Gonzalez Pavez, Ignacio Barrio, Javier Tardáguila, Talitha Venter, Carlos Poblete-Echeverria

“…Results indicate that all three models achieved high classification accuracy, with ResNet-34 obtaining the highest accuracy (97.4 % validation, 95.6 % test), reinforcing its strong feature extraction capabilities. …”
Get full text

A Multi-Epiphysiological Indicator Dog Emotion Classification System Integrating Skin and Muscle Potential Signals by Wenqi Jia, Yanzhi Hu, Zimeng Wang, Kai Song, Boyan Huang

Get full text

Experimental validation of machine learning for contamination classification of polluted high voltage insulators using leakage current by Umer Amir Khan, Mansoor Asif, Muhammad Hamza Zafar, Luai Alhems

Get full text

Integrating deep learning and transfer learning: optimizing white blood cells classification in medical educational institutions by M. Hussein, Faten Abd El-Sattar Zahran El-Mougi

“…Six architectures are evaluated: ResNet50, InceptionV3, EfficientNetB3, MobileNetV3, Swin Transformer, and a custom convolutional neural network (CNN). …”
Get full text

Peatland pixel-level classification via multispectral, multiresolution and multisensor data using convolutional neural network by Luca Zelioli, Fahimeh Farahnakian, Maarit Middleton, Timo P. Pitkänen, Sakari Tuominen, Paavo Nevalainen, Jonne Pohjankukka, Jukka Heikkonen

“…Canopy height models, Sentinel-2 bands, and Sentinel-1 bands emerged as the most influential data sources for accurate classification. …”
Get full text

Med-DGTN: Dynamic Graph Transformer with Adaptive Wavelet Fusion for multi-label medical image classification by Guanyu Zhang, Yan Li, Tingting Wang, Guokun Shi, Li Jin, Zongyun Gu, Zongyun Gu

“…IntroductionMulti-label classification of medical imaging data aims to enable simultaneous identification and diagnosis of multiple diseases, delivering comprehensive clinical decision support for complex conditions. …”
Get full text

TransFINN &#x201C;Transparent Feature Integrated Neural Network for Text Feature Selection and Classification&#x201D; by Saif Ur Rehman, Ramsha Jat, Muhammad Rafi, Jaroslav Frnda

Get full text

Real-Time Fire Risk Classification Using Sensor Data and Digital-Twin-Enabled Deep Learning by In-Seop Na, Vani Rajasekar, Velliangiri Sarveshwaran

“…Performance evaluations reveal that the DCNN+Digital twin framework achieves a 99% classification accuracy with a reduced error rate of 3% over 500 runs, outperforming standalone models, such as RNN (90% accuracy, 10% error), CNN (96% accuracy, 8% error), and DCNN (97% accuracy, 6% error). …”
Get full text

Ultrasound-based classification of follicular thyroid Cancer using deep convolutional neural networks with transfer learning by Enock Adjei Agyekum, Zhang Yuzhi, Yu Fang, Doris Nti Agyekum, Xian Wang, Eliasu Issaka, CuiRong Li, Xiangjun Shen, Xiaoqin Qian, Xinping Wu

Get full text