#7296. Progressive structure network-based multiscale feature fusion for object detection in real-time application

October 2026publication date
Proposal available till 27-05-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Control and Systems Engineering;
Electrical and Electronic Engineering;
Artificial Intelligence;
Places in the authors’ list:
place 1place 2place 3place 4
FreeFreeFreeFree
2350 $1200 $1050 $900 $
Contract №7296.1 Contract №7296.2 Contract №7296.3 Contract №7296.4
1 place - free (for sale)
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)

Abstract:
Deep learning-based target detection techniques have already made a wide-range impact on our daily life. Currently, a feature pyramid is a widely utilized technique for multiscale target detection, the effectiveness of the technique has already been proved. Nevertheless, in the pyramid structure, problems, such as multiscale feature alignment, model turmoil after fusion, feature redundancy, and no-local feature fusion, exist. In this paper, we propose a novel progressive structure network to solve the aforementioned problems.
Keywords:
Deep learning; Feature fusion; Machine learning; Object detection

Contacts :
0