A lightweight deep learning model for real-time in-vehicle driver distraction detection with low-latency inference

A comparative study of machine and deep learning models for time-series-based bearing fault diagnosis of induction motors

Kamal Hamani, Martin Kuchar, Martin Sobek, Vojtech Sotola, Petr Palacky

An explainable AI framework integrating machine and deep learning models for multi-species DNA functional group classification

Pratik Chakraborty, P. B. Shanthi

Abstract DNA functional group classification across species plays a crucial role in understanding genetic diversity, evolutionary relationships and biological function. The increasing availability of genomic data has led to the use of machine learning and deep learning methods fo…Read more

CT imaging-based radiomics and deep learning models for predicting chemotherapy response in advanced pancreatic cancer

Zhu Y, H J Zhou, Peng An, Yingfan Mao, Ziwei Nie, Yi-Xiang Wang, et al.

To investigate the value of radiomics and deep learning features derived from pre-treatment CT imaging in predicting the efficacy of chemotherapy in patients with advanced pancreatic cancer. The retrospective study included 207 patients with advanced pancreatic cancer from two me…Read more

Hybrid deep learning framework for detection of lateral movement in advanced persistent threats

Balaganesh Bojarajulu, M. Sethumadhavan, Vasily Sachnev, P. P. Amritha

Advanced persistent threats often use stolen or legitimate credentials to move stealthily across networks, making them difficult to detect with traditional security systems. This study introduces a novel framework called dual classifier-based lateral movement detection (DC-LMD-AP…Read more

Automated assessment of the ulcerative colitis endoscopic index of severity using a multi-task deep learning model

Bing Lv, Qiang Zheng, Xinxin Li, Tao Tao, Jianmin Wu, Yanting Shi

Assessment of the Ulcerative Colitis Endoscopic Index of Severity (UCEIS) is limited by subjectivity and interobserver variability. We developed UC-MTLNet, a multi-task deep learning model to predict UCEIS descriptors, total score, endoscopic remission, and severity strata. This…Read more

Hybrid fusion of E-nose and computer vision using optimized deep learning and machine learning for robust plant leaf recognition

Pouya Bohlol, Mohammad Hasan Sabet Dizavandi, Syed Saeid Mohtasebi, Mahmoud Omid

Abstract The fusion multi-sensory system with optimized deep learning and machine learning algorithms appeared to synergize difficult paradigms in precision agriculture and boost recognition of various plant species. In this study, an electronic nose (E-nose) system with eight MO…Read more