In contrast, deep learning techniques learn complex patterns from large datasets without explicit feature extraction techniques and are well-suited for disease detection tasks. This systematic review explores various deep learning approaches used in the literature for rice leaf disease detection, such as ...
Deep learning algorithms seem to achieve a particularly remarkable performance, suggesting that the implementation of clinical devices for seizure prediction might be within reach. However, most of the research evaluated the robustness of automatic forecasting methods through randomized cross-validati...
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NITW-FDP-Advance-AI-ML Public NITW Workshop on Advance AI/ML Jupyter Notebook 13 contributions in the last year Contribution Graph Day of Week February Feb March Mar April Apr May May June Jun July Jul August Aug September Sep October Oct November Nov December Dec January Jan February...
摘要: Indian conglomerate Reliance Industries and BP have submitted what is understood to be the last of three development plans for new deepwater gas fields in block KGD6 off the east coast of India. A spokesperson for Reliance confirmed the field development plan (FDP) for the MJ-1 field ...
This document is a retraction and replacement of a previous study titled "A deep learning architecture for metabolic pathway prediction." The authors discovered that the dataset used in the study contained duplicates in the multi-class classification setting. They revi...
According to news reporting originating in West Lafayette, Indiana, by NewsRx journalists, research stated, "Energy-Dissipative Evolutionary Deep Operator Neural Network is an operator learning neural network. It is designed to seek numerical solutions for a class of partial differential equations ...