Group-split attention network for crowd counting

W Zhai, M Gao, M Anisetti, Q Li… - Journal of Electronic …, 2022 - spiedigitallibrary.org
Crowd counting is a considerable yet challenging task in intelligent video surveillance and
urban security systems. The performance has been significantly boosted along with the …

[PDF][PDF] DL-HAR: deep learning-based human activity recognition framework for edge computing

A Gumaei, M Al-Rakhami, H AlSalman… - … Materials & Continua, 2020 - cdn.techscience.cn
Human activity recognition is commonly used in several Internet of Things applications to
recognize different contexts and respond to them. Deep learning has gained momentum for …

Deep learning in astronomy: a tutorial perspective

SK Meher, G Panda - The European Physical Journal Special Topics, 2021 - Springer
Astronomy is a branch of science that covers the study and analysis of all extraterrestrial
objects and their phenomena. The study brings together the aspects of mathematics …

[HTML][HTML] Enhanced DSSM (deep semantic structure modelling) technique for job recommendation

R Mishra, S Rathi - Journal of King Saud University-Computer and …, 2022 - Elsevier
Now a day's recommendation system take care of the issue of the massive amount of
information overload problem and it provides the services to the candidates to concentrate …

[HTML][HTML] Cloud and edge computing-based computer forensics: Challenges and open problems

V Prakash, A Williams, L Garg, C Savaglio, S Bawa - Electronics, 2021 - mdpi.com
In recent years, there has been a dramatic change in attitude towards computers and the
use of computer resources in general. Cloud and Edge computing have emerged as the …

A roadmap to data science: background, future, and trends

MA Khder, SW Fujo, MA Sayfi - International Journal of …, 2021 - inderscienceonline.com
Data science is a combination of several disciplines that aims to get accurate insights from a
bunch of data, develop the technology, and algorithm to solve the complicated problems …

[HTML][HTML] Machine learning and big data in the impact literature. A bibliometric review with scientific mapping in Web of Science

J López Belmonte, A Segura-Robles… - Symmetry, 2020 - mdpi.com
Combined use of machine learning and large data allows us to analyze data and find
explanatory models that would not be possible with traditional techniques, which is basic …

[HTML][HTML] Classifying ingestive behavior of dairy cows via automatic sound recognition

G Li, Y Xiong, Q Du, Z Shi, RS Gates - Sensors, 2021 - mdpi.com
Determining ingestive behaviors of dairy cows is critical to evaluate their productivity and
health status. The objectives of this research were to (1) develop the relationship between …

Advanced big-data/machine-learning techniques for optimization and performance enhancement of the heat pipe technology–A review and prospective study

Z Wang, X Zhao, Z Han, L Luo, J Xiang, S Zheng, G Liu… - Applied Energy, 2021 - Elsevier
A heat pipe (HP) is a passive heat transfer device able to transmit heat a few meters or
several hundred meters away from the heat source without use of external energy. This …

Surface Defect Detection with Modified Real‐Time Detector YOLOv3

Z Wang, H Zhu, X Jia, Y Bao, C Wang - Journal of Sensors, 2022 - Wiley Online Library
In this paper, a modified YOLOv3 net has been proposed for surface defect detection.
Different from other pixel‐level segmenting methods, YOLOv3 locates the regions of surface …