adaptive coherence estimator (ace) Search Results


adaptive coherence estimator (ace)  (CEM Corporation)
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CEM Corporation adaptive coherence estimator (ace)
Detection comparison among global, local target detection, SegNet, U-Net, and our proposed deep learning models of Area 1 without sparse enhancement (SE).
Adaptive Coherence Estimator (Ace), supplied by CEM Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Detection comparison among global, local target detection, SegNet, U-Net, and our proposed deep learning models of Area 1 without sparse enhancement (SE).

Journal: Sensors (Basel, Switzerland)

Article Title: Hybrid Deep Learning Models with Sparse Enhancement Technique for Detection of Newly Grown Tree Leaves

doi: 10.3390/s21062077

Figure Lengend Snippet: Detection comparison among global, local target detection, SegNet, U-Net, and our proposed deep learning models of Area 1 without sparse enhancement (SE).

Article Snippet: To compare with prior studies, in References [ , , ], the global and local target detection results including Adaptive Coherence Estimator (ACE), Target Constrained Interference Minimized Filter (TCIMF), Constrained Energy Minimization (CEM), Subset CEM, Sliding Window-CEM (SW CEM), Adaptive Sliding Window-CEM (ASW CEM), and Weighted Background Suppression (WBS) version of above detectors were used for comparison.

Techniques: Comparison

Detection comparison among the global and local target detection results, SegNet, U-Net, and our proposed deep learning models of Area 2 without SE.

Journal: Sensors (Basel, Switzerland)

Article Title: Hybrid Deep Learning Models with Sparse Enhancement Technique for Detection of Newly Grown Tree Leaves

doi: 10.3390/s21062077

Figure Lengend Snippet: Detection comparison among the global and local target detection results, SegNet, U-Net, and our proposed deep learning models of Area 2 without SE.

Article Snippet: To compare with prior studies, in References [ , , ], the global and local target detection results including Adaptive Coherence Estimator (ACE), Target Constrained Interference Minimized Filter (TCIMF), Constrained Energy Minimization (CEM), Subset CEM, Sliding Window-CEM (SW CEM), Adaptive Sliding Window-CEM (ASW CEM), and Weighted Background Suppression (WBS) version of above detectors were used for comparison.

Techniques: Comparison