Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Jiulu Gong"'
Publikováno v:
Entropy, Vol 26, Iss 6, p 468 (2024)
Block compressed sensing (BCS) is a promising method for resource-constrained image/video coding applications. However, the quantization of BCS measurements has posed a challenge, leading to significant quantization errors and encoding redundancy. In
Externí odkaz:
https://doaj.org/article/79af6c8b7f3f478e882d5ad5e4e64e3e
Publikováno v:
Remote Sensing, Vol 16, Iss 3, p 573 (2024)
Due to the influence of the complex background of airports and damaged areas of the runway, the existing runway extraction methods do not perform well. Furthermore, the accurate crater extraction of airport runways plays a vital role in the military
Externí odkaz:
https://doaj.org/article/f95c156f19c540f3a63e23799460351c
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2020, Iss 1, Pp 1-19 (2020)
Abstract Many objects in real world have circular feature. It is a difficult task to obtain the 2D-3D pose estimation using circular feature in challenging scenarios. This paper proposes a method to incorporate elliptic shape prior for object pose es
Externí odkaz:
https://doaj.org/article/e57fdb5cda4b4b61b56fc5995e0bc41b
Publikováno v:
Sensors, Vol 22, Iss 13, p 4806 (2022)
Block compressed sensing (BCS) is suitable for image sampling and compression in resource-constrained applications. Adaptive sampling methods can effectively improve the rate-distortion performance of BCS. However, adaptive sampling methods bring hig
Externí odkaz:
https://doaj.org/article/6cb58a09b2dc45fd813154075cc45baa
Publikováno v:
Entropy, Vol 23, Iss 10, p 1354 (2021)
Block compressed sensing (BCS) is a promising technology for image sampling and compression for resource-constrained applications, but it needs to balance the sampling rate and quantization bit-depth for a bit-rate constraint. In this paper, we summa
Externí odkaz:
https://doaj.org/article/4a76d4be0bfc491db84b67a8a09f2ee2
Publikováno v:
Applied Sciences, Vol 10, Iss 17, p 6053 (2020)
Detecting small objects and objects with large scale variants are always challenging for deep learning based object detection approaches. Many efforts have been made to solve these problems such as adopting more effective network structures, image fe
Externí odkaz:
https://doaj.org/article/6118828fddf04d45928d7c61a0b8ed1d
Publikováno v:
Entropy, Vol 22, Iss 1, p 125 (2020)
Compressed sensing (CS) offers a framework for image acquisition, which has excellent potential in image sampling and compression applications due to the sub-Nyquist sampling rate and low complexity. In engineering practices, the resulting CS samples
Externí odkaz:
https://doaj.org/article/7ae19030fb7848919767af64346c633c
Publikováno v:
Sensors, Vol 15, Iss 5, Pp 10118-10145 (2015)
We propose new techniques for joint recognition, segmentation and pose estimation of infrared (IR) targets. The problem is formulated in a probabilistic level set framework where a shape constrained generative model is used to provide a multi-class a
Externí odkaz:
https://doaj.org/article/b9c54f6c60b34d5798f1aa918824f7c3
Publikováno v:
Sensors, Vol 14, Iss 6, Pp 10124-10145 (2014)
We propose a new integrated target tracking, recognition and segmentation algorithm, called ATR-Seg, for infrared imagery. ATR-Seg is formulated in a probabilistic shape-aware level set framework that incorporates a joint view-identity manifold (JVIM
Externí odkaz:
https://doaj.org/article/81c5f87d56ad4f999978744a7294eda1
Publikováno v:
2022 IEEE International Conference on Unmanned Systems (ICUS).