IndraLab

Statements


| 13

sparser
"The results showed the conservation of 2 to 5 domains, characterized by the presence of STKc_CAMK, a calmodulin-like domain (CAM-LD), and EF-hands."

sparser
"Specifically, the CAM-LD directly binds calcium, inducing intramolecular conformational changes that result in calcium-specific activation of the catalytic domain [ xref ]."

sparser
"Additionally, CDPKs possess a bipartite nuclear localization signal sequence as a subdomain in their JD, which indicates the absence of consensus binding sites in their respective CAM-LD [ xref , xref , xref ]."

sparser
"Lane Detection with Convolutional Attention Mechanism (LD-CAM) model is proposed to achieve this outcome."

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"Proposed LD-CAM Architecture for Lane Detection."

sparser
"An LD-CAM architecture for lane detection in unstructured roads is proposed in this work."

sparser
"The pre-processed image is then fed to LD-CAM architecture which consists of an encoder, Enhanced Convolutional Block Attention modules (E-CBAM), and a decoder."

sparser
"Figure  xref depicts the general framework of proposed LD-CAM Architecture."

sparser
"Significant findings are shown by comparing the performance of several models, such as U-net, Encoder-decoder SegNet VGG16, SCNN Unet Light ConvGRU, SCNN Unet Light ConvLSTM, SHPDAN (Spatial Hierarchical Dilated Attention Network) and the proposed LD-CAM architecture."

sparser
"Nevertheless, with an accuracy of 97.90%, precision of 98.92%, recall of 98.8%, and an F1 score of 97.70%, the proposed LD-CAM architecture performs better than the other existing models."

sparser
"This results demonstrate LD-CAM’s sophisticated ability to precisely detect essential characteristics while reducing false positives and negatives."

sparser
"Though the LD-CAM model shows promising results its computational complexity may increase due to introduction of enhanced convolutional attention mechanism (E-CBAM), while deployed in low power embedded systems commonly used in autonomous vehicles."

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"By addressing these limitations, we aim to further enhance the robustness and applicability of the proposed LD-CAM model in real-world autonomous driving scenarios."