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Multi-class skin cancer classification architecture based on deep convolutional neural network
Skin cancer is a deadly disease. Melanoma is a type of skin cancer responsible for the high
mortality rate. Early detection of skin cancer can enable patients to treat the disease and …
mortality rate. Early detection of skin cancer can enable patients to treat the disease and …
Quantifying imbalanced classification methods for leukemia detection
Uncontrolled proliferation of B-lymphoblast cells is a common characterization of Acute
Lymphoblastic Leukemia (ALL). B-lymphoblasts are found in large numbers in peripheral …
Lymphoblastic Leukemia (ALL). B-lymphoblasts are found in large numbers in peripheral …
Microscopy analysis neural network to solve detection, enumeration and segmentation from image-level annotations
The development of deep learning approaches to detect, segment or classify structures of
interest has transformed the field of quantitative microscopy. High-throughput quantitative …
interest has transformed the field of quantitative microscopy. High-throughput quantitative …
Automatic patient-level recognition of four Plasmodium species on thin blood smear by a real-time detection transformer (RT-DETR) object detection algorithm: a …
E Guemas, B Routier… - Microbiology …, 2024 - journals.asm.org
Malaria remains a global health problem, with 247 million cases and 619,000 deaths in
2021. Diagnosis of Plasmodium species is important for administering the appropriate …
2021. Diagnosis of Plasmodium species is important for administering the appropriate …
CellSegUNet: an improved deep segmentation model for the cell segmentation based on UNet++ and residual UNet models
S Metlek - Neural Computing and Applications, 2024 - Springer
Cell nucleus segmentation is an important method that is widely used in the diagnosis and
treatment of many diseases, as well as counting and identifying the cell nucleus. The main …
treatment of many diseases, as well as counting and identifying the cell nucleus. The main …
Handwritten word recognition using deep learning approach: A novel way of generating handwritten words
A handwritten word recognition system comes with issues such as-lack of large and diverse
datasets. It is necessary to resolve such issues since millions of official documents can be …
datasets. It is necessary to resolve such issues since millions of official documents can be …
Deep learning approach for classifying the aggressive comments on social media: Machine translated data vs real life data
Aggressive comments on social media negatively impact human life. Such offensive
contents are responsible for depression and suicidal-related activities. Since online social …
contents are responsible for depression and suicidal-related activities. Since online social …
Morphology classification of malaria infected red blood cells using deep learning techniques
Malaria is an endemic disease that causes great harm to children and pregnant women.
Without early and proper diagnosis, it leads to organ failure, coma and eventually death. The …
Without early and proper diagnosis, it leads to organ failure, coma and eventually death. The …
Software supply chain vulnerabilities detection in source code: Performance comparison between traditional and quantum machine learning algorithms
The software supply chain (SSC) attack has become one of the crucial issues that are being
increased rapidly with the advancement of the software development domain. In general …
increased rapidly with the advancement of the software development domain. In general …
Automatic penaeus monodon larvae counting via equal keypoint regression with smartphones
X Li, R Liu, Z Wang, G Zheng, J Lv, L Fan, Y Guo… - Animals, 2023 - mdpi.com
Simple Summary To enhance farming efficiency, most farmers prefer to purchase Penaeus
larvae as opposed to hatching them themselves. However, counting small and highly …
larvae as opposed to hatching them themselves. However, counting small and highly …