Automatic modulation classification (AMC) is an essential technology in modern communications, enabling the identification of various signal modulation schemes without prior knowledge, thereby ...
Traffic classification is a crucial task for network security. One of the most difficult challenges is to accurately identify the traffic of unknown applications as well as discriminate the known ...
In traditional semiconductor packaging, manual defect review after automated optical inspection (AOI) is an arduous task for operators and engineers, involving review of both good and bad die. It is ...
Using whole-slide hematoxylin and eosin images from 214 patients with glioblastoma in The Cancer Genome Atlas (TCGA), a fine-tuned convolutional neural network model extracted deep learning features.
However, in indoor environments, non-line-of-sight (NLOS) signals significantly degrade the ranging performance of UWB ...
Effect of breast tissue density on cell-free orphan non-coding RNAs secreted by breast cancers. Nature and distribution of methyl thioadenosine phosphorylase (MTAP) genomic loss in human tumors. This ...
This study presents a deep learning model for breast cancer detection, achieving 99.24% accuracy and improving clinical decision-making through image retrieval.
Overview Neural networks courses in 2026 focus heavily on practical deep learning frameworks such as TensorFlow, PyTorch, and Keras.Growing demand for AI profes ...
Recent advances in deep learning have significantly transformed mineral classification methodologies, supplanting labour‐intensive manual approaches with automated, high-precision systems. By ...
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