Predicting and Preventing Crime: A Crime Prediction Model Using San Francisco Crime Data by Classification Techniques by Muzammil Khan, Azmat Ali, Yasser Alharbi

“…The crime is difficult to predict; it is random and possibly can occur anywhere at any time, which is a challenging issue for any society. The study proposes a crime prediction model by analyzing and comparing three known prediction classification algorithms: Naive Bayes, Random Forest, and Gradient Boosting Decision Tree. …”
Get full text

Utilizing Machine Learning-based Classification Models for Tracking Air Pollution Sources: A Case Study in Korea by Yelim Choi, Bogyeong Kang, Daekeun Kim

“…This study aims to comprehensively evaluate machine learning-based emission source classification models to provide insights into air pollution source tracking and management. …”
Get full text

DynGraph-BERT: Combining BERT and GNN Using Dynamic Graphs for Inductive Semi-Supervised Text Classification by Eliton Luiz Scardin Perin, Mariana Caravanti de Souza, Jonathan de Andrade Silva, Edson Takashi Matsubara

“…The combination of Bidirecional Encoder Representations from Transformers (BERT) and Graph Neural Networks (GNNs) has been extensively explored in the text classification literature, usually employing BERT as a feature extractor combined with heterogeneous static graphs. …”
Get full text

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

“…To overcome this issue, we propose a local auxiliary spatial–spectral decoupling transformer network to ease the learning of global domain-invariant information. …”
Get full text

Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray. by Nadim Rana, Yahaya Coulibaly, Ayman Noor, Talal H Noor, Md Imran Alam, Zeba Khan, Ali Tahir, Mohammad Zubair Khan

“…Thus, in this research, a model for thorax disease classification using Chest X-rays is proposed by considering deep learning model. …”
Get full text

Real-time bearing fault classification of induction motor using enhanced inception ResNet-V2 by Karan Kumar K, Srihari Mandava

“…However, it is challenging to use Deep Learning techniques to identify bearing defects when the machine is not under load. To resolve this issue, this paper presents the Constant-Q Non-stationary Gabor Transform with enhanced Inception ResNet-V2, proposed for the early-stage classification of ball bearing faults in induction motors. …”
Get full text

Addressing long-tailed distribution in judicial text for criminal motive classification: a balanced contrastive learning approach by Ting Li, Lewen Mi, Xiangyu Meng, Yongju Jia, Lin Zhao, Qi Zhao, Zihao Wei, Guandong Gao, Xiangxian Li

“…Specifically, CA-BCL first balances the sampling process to alleviate the class imbalance during prototype construction and then applies balanced contrastive learning to improve the model’s ability to generalize to long-tailed categories, leading to better overall classification performance. Our experimental results demonstrate that CA-BCL significantly outperforms existing text classification models in crime motive classification, while also showing strong generalization capabilities on standard text classification benchmark.…”
Get full text

K-Nearest Neighbor and Naive Bayes Classifier Algorithm in Determining The Classification of Healthy Card Indonesia Giving to The Poor by Yofi Firdan Safri, Riza Arifudin, Much Aziz Muslim

Get full text

Malignant lymphoma in Eastern India: A retrospective analysis of 455 cases according to World Health Organization classification by Santosh Kumar Mondal, Palash Kumar Mandal, Tarun Kumar Samanta, Subrata Chakaborty, Saptarshi Dutta Roy, Shravasti Roy

Get full text

Bathymetry-guided multi-source remote sensing image domain adaptive coral reef benthic habitat classification by Hui Chen, Liang Cheng, Ka Zhang

“…Due to the complexity of marine environments, multi-source remote sensing images often exhibit significant domain shifts caused by differences in imaging conditions and platform orientations, posing challenges to the generalization of substrate classification models. To address this issue, we propose a computationally efficient Bathymetry-Guided Domain Adaptation (BGDA) method. …”
Get full text

Corporate Governance And Its Effect On Professional Performance In Palestinian Private Universities, In Light Of Quality, Accreditation, And Classification Requirements by Dr. Issam Buhaisi, Dr. Zyad Al Damagh

“…The purpose of the study is to examine the actual status of corporate governance principles in Palestinian private universities at Gaza Strip Governorates, in order to propose a framework of governance for these universities, in light of quality, accreditation and classification requirements for Palestinian universities issued by Palestinian Ministry of Higher Education. …”
Get full text

Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…This work compares and reports the classification, machine learning, and deep learning algorithms that predict cardiovascular illnesses. …”
Get full text

Comparison of the performance of three classification criteria for Behçet's Disease in a single centre cohort from South India by Vishnu S Chandran, Suma Balan

Get full text

Land use and land cover classification and terrestrial ecosystem carbon storage changes in Vietnam based on Sentinel images by Yang Liu, Kun Yang, Zongqi Peng, Tianle Zou, Danni Su, Run Sun, Jingcong Ma

“…This study developed a new land cover classification method based on the phenological characteristics of rice, using the Google Earth Engine (GEE). …”
Get full text

An Exploration of Students’ Misconceptions about the Concept ‘Classification of Animals’ at Secondary Level and Effectiveness of Inquiry Method for Conceptual Change by Anjum NAZ, Abida NASREEN

Get full text

SwinConvNeXt: a fused deep learning architecture for Real-time garbage image classification by B. Madhavi, Mohan Mahanty, Chia-Chen Lin, B. Omkar Lakshmi Jagan, Hari Mohan Rai, Saurabh Agarwal, Neha Agarwal

“…The conventional method of segregating waste is a time-consuming and ineffective method that wastes human power and money. To address this issue in real time, sophisticated and sustainable waste management systems need to be implemented. …”
Get full text

Hybrid Deep Learning Approach for Accurate Detection and Multiclass Classification of Broken Conductor Faults in Power Distribution Systems by Firas Saadoon Mohammed Al-Jumaili, Mustafa Onat

“…The identification and classification of broken conductor faults in power distribution systems (PDSs) is challenging because of the nonlinear and complex nature of the unbalanced three-phase currents. …”
Get full text

Coastal Wetlands Classification and Carbon Storage Estimation: A Case Study of the Region Surrounding the South China Sea by Guanglin Lai, Zhi He, Chengle Zhou, Youwei Wang

“…However, designing a DL method that is both easily trainable and suitable for large-scale coastal wetland classification remains a challenging issue. This article proposes a novel DL method and a new carbon correction strategy for large-scale coastal wetland classification and carbon storage assessment. …”
Get full text

Deep Learning Architecture to Infer Kennedy Classification of Partially Edentulous Arches Using Object Detection Techniques and Piecewise Annotations by Zohaib Khurshid, MRes, FDTFEd, FHEA, Maria Waqas, PhD, Shehzad Hasan, PhD, Shakeel Kazmi, PhD, Muhammad Faheemuddin, FCPS

“…Objectives: Dental health is integral to overall well-being, with early detection of issues critical for prevention. This research work focuses on utilizing artificial intelligence and deep learning–based object detection techniques for automated detection of common dental issues in orthopantomography x-ray images, including broken roots, periodontally compromised teeth, and the Kennedy classification of partially edentulous arches. …”
Get full text

Dual-Alignment CLIP: Task-Specific Alignment of Text and Visual Features for Few-Shot Remote Sensing Scene Classification by Dongmei Deng, Ping Yao

“…Inspired by human ability, few-shot image classification offers a promising solution by utilizing limited labeled data. …”
Get full text