Artificial intelligence and deep learning have revolutionized the field of neural data analysis in recent years. The explosion of complex, high-dimensional ...
Abstract: In this article, a framework for the analog implementation of a deep convolutional neural network (CNN) is introduced and used to derive a new circuit architecture which is composed of an ...
Abstract: Acute Lymphoblastic Leukemia (ALL) is a serious blood cancer characterized by the abnormal growth of progenitor white blood cells, which interferes with normal blood cell production. Early ...
Abstract: Accurate gas volume fraction (GVF) measurement in gas-liquid two-phase flow remains a key challenge in industrial process monitoring and control. In order to address this, a deep ...
Abstract: A fused feature set for recognition of Meitei Mayek handwritten characters is presented in this paper. The approach combines traditional hand-crafted feature and deep feature descriptors ...
Abstract: Orthogonal time frequency space (OTFS) modulation has emerged as a promising paradigm for 6G communications due to its inherent adaptability to rapidly time-varying multipath channels.
Abstract: When it comes to studying environmental problems, it is growing increasingly vital to discover climatic anomalies and measure temperature changes, particularly in areas like Ethiopia, where ...
Soybean is one of the world’s major oil-bearing crops and occupies an important role in the daily diet of human beings. However, the frequent occurrence of soybean leaf diseases caused serious threats ...
Abstract: Early detection of tsunamis is essential for disaster risk reduction and minimizing loss of life. This research introduces an advanced deep learning-based tsunami detection model that ...
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