Comparative Study
Comparative studies are a cornerstone of scientific advancement, rigorously evaluating different approaches to solve a problem or understand a phenomenon. Current research focuses on comparing various machine learning models (e.g., CNNs, Transformers, LLMs, and GANs) across diverse applications, including image classification, natural language processing, and optimization problems. These comparisons often involve analyzing the impact of different hyperparameters, data augmentation techniques, and training strategies on model performance and efficiency, leading to improved algorithms and more effective solutions. The insights gained from these studies are crucial for advancing both theoretical understanding and practical applications across numerous scientific disciplines and industrial sectors.
Papers
Comparative Analysis of Machine Learning and Deep Learning Models for Classifying Squamous Epithelial Cells of the Cervix
Subhasish Das, Satish K Panda, Madhusmita Sethy, Prajna Paramita Giri, Ashwini K Nanda
Comparative Analysis of Audio Feature Extraction for Real-Time Talking Portrait Synthesis
Pegah Salehi, Sajad Amouei Sheshkal, Vajira Thambawita, Sushant Gautam, Saeed S. Sabet, Dag Johansen, Michael A. Riegler, Pål Halvorsen
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models
Nandavardhan R., Somanathan R., Vikram Suresh, Savaridassan P
Emotion Detection in Reddit: Comparative Study of Machine Learning and Deep Learning Techniques
Maliheh Alaeddini
Face De-identification: State-of-the-art Methods and Comparative Studies
Jingyi Cao, Xiangyi Chen, Bo Liu, Ming Ding, Rong Xie, Li Song, Zhu Li, Wenjun Zhang
A Comparative Study of Discrete Speech Tokens for Semantic-Related Tasks with Large Language Models
Dingdong Wang, Mingyu Cui, Dongchao Yang, Xueyuan Chen, Helen Meng
Impact of Iris Pigmentation on Performance Bias in Visible Iris Verification Systems: A Comparative Study
Geetanjali Sharma, Abhishek Tandon, Gaurav Jaswal, Aditya Nigam, Raghavendra Ramachandra
A Comparative Study of Deep Reinforcement Learning for Crop Production Management
Joseph Balderas, Dong Chen, Yanbo Huang, Li Wang, Ren-Cang Li
A Comparative Study of Recent Large Language Models on Generating Hospital Discharge Summaries for Lung Cancer Patients
Yiming Li, Fang Li, Kirk Roberts, Licong Cui, Cui Tao, Hua Xu