|
|
|
|
|
Ru Ye, Hongyan Xing and Xing Zhou
Addressing the limitations of manually extracting features from small maritime target signals, this paper explores Markov transition fields and convolutional neural networks, proposing a detection method for small targets based on an improved Markov tran...
ver más
|
|
|
|
|
|
|
|
|
Hasan Mhd Nazha, Mhd Ayham Darwich, Basem Ammar, Hala Dakkak and Daniel Juhre
An investigation was conducted to examine the photothermal and thermomechanical effects of short-pulse laser irradiation on normal tissues. This study analyzed the impact of short-pulse laser radiation on the heat-affected region within tissues, taking i...
ver más
|
|
|
|
|
|
|
|
|
Norah Fahd Alhussainan, Belgacem Ben Youssef and Mohamed Maher Ben Ismail
Brain tumor diagnosis traditionally relies on the manual examination of magnetic resonance images (MRIs), a process that is prone to human error and is also time consuming. Recent advancements leverage machine learning models to categorize tumors, such a...
ver más
|
|
|
|
|
|
|
|
|
Seokjoon Kwon, Jae-Hyeon Park, Hee-Deok Jang, Hyunwoo Nam and Dong Eui Chang
Deep learning algorithms are widely used for pattern recognition in electronic noses, which are sensor arrays for gas mixtures. One of the challenges of using electronic noses is sensor drift, which can degrade the accuracy of the system over time, even ...
ver más
|
|
|
|
|
|
|
|
|
Tianyu Dong, Jiazu Zhou, Junfan Zhuo, Bo Li and Feng Zhu
Conventional traffic stability studies primarily concentrate on the evolution of disturbances in vehicle motion but seldom consider how collision risk changes spatially and temporally. This study bridges the gap by extending the principles of traffic sta...
ver más
|
|
|
|