Facial emotion recognition based on biorthogonal wavelet entropy, fuzzy support vector machine, and stratified cross validation
Emotion recognition represents the position and motion of facial muscles. It contributes
significantly in many fields. Current approaches have not obtained good results. This paper …
significantly in many fields. Current approaches have not obtained good results. This paper …
Evolution of multiorgan segmentation techniques from traditional to deep learning in abdominal CT images–A systematic review
H Kaur, N Kaur, N Neeru - Displays, 2022 - Elsevier
Abdominal organ segmentation is the crucial research direction in computer assisted
diagnostic systems. Segmentation of multiple organs in medical images is known as …
diagnostic systems. Segmentation of multiple organs in medical images is known as …
Density estimation of SARS-CoV2 spike proteins using super pixels segmentation technique
BA Taha, Q Al-Jubouri, Y Al Mashhadany… - Applied soft …, 2023 - Elsevier
The worldwide outbreak of COVID-19 disease was caused by the severe acute respiratory
syndrome coronavirus 2 (SARS-CoV 2). The existence of spike proteins, which allow these …
syndrome coronavirus 2 (SARS-CoV 2). The existence of spike proteins, which allow these …
Single slice based detection for Alzheimer's disease via wavelet entropy and multilayer perceptron trained by biogeography-based optimization
Detection of Alzheimer's disease (AD) from magnetic resonance images can help
neuroradiologists to make decision rapidly and avoid missing slight lesions in the brain …
neuroradiologists to make decision rapidly and avoid missing slight lesions in the brain …
Pathological brain detection by artificial intelligence in magnetic resonance imaging scanning (invited review)
(Aim) Pathological brain detection (PBD) systems aim to assist and even replace
neuroradiologists to make decisions for patients. This review offers a comprehensive and …
neuroradiologists to make decisions for patients. This review offers a comprehensive and …
Multiple sclerosis detection based on biorthogonal wavelet transform, RBF kernel principal component analysis, and logistic regression
To detect multiple sclerosis (MS) diseases early, we proposed a novel method on the
hardware of magnetic resonance imaging, and on the software of three successful methods …
hardware of magnetic resonance imaging, and on the software of three successful methods …
Fruit classification by biogeography‐based optimization and feedforward neural network
Accurate fruit classification is difficult to accomplish because of the similarities among the
various categories. In this paper, we proposed a novel fruit‐classification system, with the …
various categories. In this paper, we proposed a novel fruit‐classification system, with the …
Noise-robust hyperspectral image classification via multi-scale total variation
In this paper, a novel multi-scale total variation method is proposed to extract structural
features from hyperspectral images (HSIs), which consists of the following steps. First, the …
features from hyperspectral images (HSIs), which consists of the following steps. First, the …
Automatic 2-D/3-D vessel enhancement in multiple modality images using a weighted symmetry filter
Automated detection of vascular structures is of great importance in understanding the
mechanism, diagnosis, and treatment of many vascular pathologies. However, automatic …
mechanism, diagnosis, and treatment of many vascular pathologies. However, automatic …
Seven-layer deep neural network based on sparse autoencoder for voxelwise detection of cerebral microbleed
In order to detect the cerebral microbleed (CMB) voxels within brain, we used susceptibility
weighted imaging to scan the subjects. Then, we used undersampling to solve the accuracy …
weighted imaging to scan the subjects. Then, we used undersampling to solve the accuracy …