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MCNet: Mask Cell of Multi Class Deep Network for Blood Cells Detection and Classification
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Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance segmentation process based on classification confidence. Here, we consider the context of this problem and present Mask Cell of multi-class deep network (MCNet) as a new network that has the module to learn about the quality of the predicted instance masks. Our proposal entails using faster R-CNN, such as segmentation on white blood cell microscope images, to accurately categorize acute lymphoblastic leukemia cases. This approach aims to enhance the efficiency and effectiveness of the diagnostic process. The suggested network block combines the instance feature with the matching anticipated mask to estimate the proposed mask IoU. In this work, we used the transfer learning approach to apply Mask R-CNN to segment white blood cells on a microscope image. To address the issue of poor lighting in stained white blood cell microscopy pictures, We included a contrast enhancement procedure in the image dataset. The comparative experiment applies YOLO v9 for classification and Mask R-CNN. The MCNet approach adjusts the discrepancy between the quality of the mask and its proposed detection, enhancing the effectiveness of instance segmentation. The final results for two datasets trained using PBC and BCCD are as follows: the accuracy of mAP@IoU 0.50 for the PBC dataset is 95.70, while the Accuracy for the BCCD dataset is 96.76, with recall and precision both coming in at 97.23 and 96.72, respectively.

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Publication Date
Fri Jul 17 2026
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, Issn 1886-8576, Vol. 18, Nº. 3, 2023, Págs. 319-323
The Effect of Using Exercises Associated With Ischemia and Hyperemia on Some Immunoglobulins (Igm - Igg) and White Blood Cells (Wbc) in the Rehabilitation and Treatment of Ankle Sprain Injury Lateral Side of Swimmers
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Autorías: Wafaa Sabah Mohammed Al-Khafaji, Fatimah Hameed Kzar Al-Masoodi, Suadad Ibrahim Suhail Al-Kinani. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 3, 2023. Artículo de Revista en Dialnet.

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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Educational And Psychological Researches
Strategic influence of Robinson and self questioner at progressing the reading comprehension for primary sixth class students
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Recent research looking for acknowledgment of strategically influence of Robinson and self question at progressing the reading comprehension for students of sixth class .

To achieve research goal so the researcher mentally chose primary sixth class  at  the school (Tashti the primary) that followed education directorate of province (Jamjamal)/Suliymania for the scholastic year 2012-2013 as application field for their experiment of boys' number reached to (95) (female and male)students in reality (32) of the first experimental group and (31) student (female and male) from controlled group, the researcher rewarded between of three variable groups (timing period, intelligence ,Kurdish language degr

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Publication Date
Tue Jul 01 2025
Journal Name
Ain Shams Engineering Journal
Deep neural networks for speech enhancement and speech recognition: A systematic review
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Publication Date
Tue Jul 01 2025
Journal Name
Ain Shams Engineering Journal
Deep neural networks for speech enhancement and speech recognition: A systematic review
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Publication Date
Sun Dec 04 2011
Journal Name
Baghdad Science Journal
Modifying Hebbian Network for Text Cipher
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The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. This work modernize the feedforward neural network, so the secret message will be encrypted by unsupervised neural network method to get the cipher text that can be decrypted using the same network to get the original text. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding lengths. In this work, the key is the final weights

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Wed Sep 29 2021
Journal Name
Biomass Conversion And Biorefinery
Encapsulated deep eutectic solvent for esterification of free fatty acid
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A novel encapsulated deep eutectic solvent (DES) was introduced for biodiesel production via a two-step process. The DES was encapsulated in medical capsules and were used to reduce the free fatty acid (FFA) content of acidic crude palm oil (ACPO) to the minimum acceptable level (< 1%). The DES was synthesized from methyltriphenylphosphonium bromide (MTPB) and p-toluenesulfonic acid (PTSA). The effects pertaining to different operating conditions such as capsule dosage, reaction time, molar ratio, and reaction temperature were optimized. The FFA content of ACPO was reduced from existing 9.61% to less than 1% under optimum operating conditions. This indicated that encapsulated MTPB-DES performed high catalytic activity in FFA esterificatio

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Publication Date
Sat Oct 12 2019
Journal Name
Journal Of Engineering And Applied Sciences
Characterization of (CIGS)/(CdS) Hetrojunction for Solar Cell
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The CIGS/CdS p-n junction thin films were fabricated and deposited at room temperature with rate of deposition 5, and 6 nm secG1 , on ITO glass substrates with 1mm thickness by thermal evaporation technique at high vacuum pressure 2×10G5 mbar, with area of 1 cm2 and Aluminum electrode as back contact. The thickness of absorber layer (CIGS) was 1 µm while the thickness of the window layer CdS film was 300 nm. The X-ray Diffraction results have shown that all thin films were polycrystalline with orientation of 112 and 211 for CIGS thin films and 111 for CdS films. The direct energy gaps for CIGS and CdS thin films were 1.85 and 2.4 eV, respectively. Atomic Force Microscopy measurement proves that both films CIGS and CdS films have nanostru

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Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Physics: Conference Series
Construction of ZnO-Nanoflowers Photoanode for Photoelectrochemical Cell
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Abstract<p>ZnO-nanoflowers on a transparent conductive tin-doped In<sub>2</sub>O<sub>3</sub> (ITO) glass substrate have been successfully prepared via a simple and efficient growth approach that is combining of dip coating and hydrothermal processes. One thin layer of ZnO nanoparticles is prepared by dip coating method followed by hydrothermally grown of ZnO nanoflowers at low temperature. The morphology and structure of ZnO-nanoflowers were inspected by field-emission scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD), respectively. The optical absorption and photoluminescence spectra of ZnO-nanoflowers are also investigated. The ZnO-nanoflowers photoanode sho</p> ... Show More
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