A customized efficient deep learning model for the diagnosis of acute leukemia cells based on lymphocyte and monocyte images
S Ansari, AH Navin, AB Sangar, JV Gharamaleki… - Electronics, 2023 - mdpi.com
The production of blood cells is affected by leukemia, a type of bone marrow cancer or blood
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …
Automatic detection of driver fatigue based on EEG signals using a developed deep neural network
In recent years, detecting driver fatigue has been a significant practical necessity and issue.
Even though several investigations have been undertaken to examine driver fatigue, there …
Even though several investigations have been undertaken to examine driver fatigue, there …
DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning …
Identifying and verifying the identity of people based on scanned images of handwritten
documents is an applicable biometric modality with applications in forensic and historic …
documents is an applicable biometric modality with applications in forensic and historic …
Visual saliency and image reconstruction from EEG signals via an effective geometric deep network-based generative adversarial network
Reaching out the function of the brain in perceiving input data from the outside world is one
of the great targets of neuroscience. Neural decoding helps us to model the connection …
of the great targets of neuroscience. Neural decoding helps us to model the connection …
Automatically identified EEG signals of movement intention based on CNN network (End-To-End)
Movement-based brain–computer Interfaces (BCI) rely significantly on the automatic
identification of movement intent. They also allow patients with motor disorders to …
identification of movement intent. They also allow patients with motor disorders to …
Automatic Liver Tumor Segmentation from CT Images Using Graph Convolutional Network
Segmenting the liver and liver tumors in computed tomography (CT) images is an important
step toward quantifiable biomarkers for a computer-aided decision-making system and …
step toward quantifiable biomarkers for a computer-aided decision-making system and …
[HTML][HTML] Developing an efficient deep neural network for automatic detection of COVID-19 using chest X-ray images
S Sheykhivand, Z Mousavi, S Mojtahedi… - Alexandria Engineering …, 2021 - Elsevier
Abstract The novel coronavirus (COVID-19) could be described as the greatest human
challenge of the 21st century. The development and transmission of the disease have …
challenge of the 21st century. The development and transmission of the disease have …
Ensemble median empirical mode decomposition for emotion recognition using EEG signal
This letter investigates ensemble median empirical mode decomposition (MEEMD), an
extension model of ensemble empirical mode decomposition, and its improved …
extension model of ensemble empirical mode decomposition, and its improved …
Acute Leukemia Diagnosis Based on Images of Lymphocytes and Monocytes Using Type-II Fuzzy Deep Network
S Ansari, AH Navin, A Babazadeh Sangar… - Electronics, 2023 - mdpi.com
A cancer diagnosis is one of the most difficult medical challenges. Leukemia is a type of
cancer that affects the bone marrow and/or blood and accounts for approximately 8% of all …
cancer that affects the bone marrow and/or blood and accounts for approximately 8% of all …
Qualitative Classification of Proximal Femoral Bone Using Geometric Features and Texture Analysis in Collected MRI Images for Bone Density Evaluation
M Najafi, T Yousefi Rezaii, S Danishvar, SN Razavi - Sensors, 2023 - mdpi.com
The aim of this study was to use geometric features and texture analysis to discriminate
between healthy and unhealthy femurs and to identify the most influential features. We …
between healthy and unhealthy femurs and to identify the most influential features. We …