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Found 6 papers, 1 papers with code
SEDNet: Shallow Encoder-Decoder Network for Brain Tumor Segmentation
Despite the advancement in computational modeling towards brain tumor segmentation, of which several models have been developed, it is evident from the computational complexity of existing models which are still at an all-time high, that performance and efficiency under clinical application scenarios are limited.
Convolutional Neural Network Ensemble Learning for Hyperspectral Imaging-based Blackberry Fruit Ripeness Detection in Uncontrolled Farm Environment
To address this engineering application challenge, this paper proposes a novel multi-input convolutional neural network (CNN) ensemble classifier for detecting subtle traits of ripeness in blackberry fruits.
Structure-focused Neurodegeneration Convolutional Neural Network for Modeling and Classification of Alzheimer's Disease
Therefore, our model itself as a potential brain structural change Digi-Biomarker for early diagnosis of AD.
Consensus-Threshold Criterion for Offline Signature Verification using Convolutional Neural Network Learned Representations
This presents a challenge which puts a genuine signer at risk of being denied access, while a forge signer is granted access.
Understanding Unconventional Preprocessors in Deep Convolutional Neural Networks for Face Identification
Others are termed the unconventional preprocessors, they are: color space converters; HSV, CIE L*a*b* and YCBCR, grey-level resolution preprocessors; full-based and plane-based image quantization, illumination normalization and insensitive feature preprocessing using: histogram equalization (HE), local contrast normalization (LN) and complete face structural pattern (CFSP).
Expressing Facial Structure and Appearance Information in Frequency Domain for Face Recognition
Beneath the uncertain primitive visual features of face images are the primitive intrinsic structural patterns (PISP) essential for characterizing a sample face discriminative attributes.
