Abstract: Identifying diseases in apple leaves plays a vital role in boosting farm productivity and preventing crop losses. This research introduces a comprehensive approach for classifying images of ...
Abstract: Timed observation and accurate detection of plant diseases is vital for minimizing the damage to the crops and securing food for the long term, but particularly with cherry powdery mildew ...
Abstract: Electrical impedance tomography (EIT) has garnered increasing attention in recent years, across different domains, as a promising alternative to traditional imaging techniques like X-rays ...
Abstract: In the realm of millimeter wave (mmWave) communication, massive multiple-input-multiple-output (mMIMO) systems have grabbed greater attention due to advancements in the 5G cellular networks.
Abstract: In this paper, we proposed a novel deep learning framework, the Synergistic Deep Learning Model, for recognizing copyrighted characters with heightened accuracy and minimized overfitting.
Abstract: This paper presents a novel deep learning framework for classifying Babylonian numerals by integrating Convolutional Neural Networks (CNNs) with a hybrid CNN-SVM model. The core ...
An accurate assessment of the state of health (SOH) is the cornerstone for guaranteeing the long-term stable operation of ...