jiang-li-321's Stars
SatyanarayanaVelamala/Rock-Identification-Using-Deep-Convolution-Neural-Network
Rocks are a fundamental component of Earth. The automatic identification of rock type in the field would aid geological surveying, education, and automatic mapping. It is a basic part of geological surveying and research, and mineral resources exploration. The automatic identification of rock type in the field would aid geological surveying, education, and automatic mapping. Working conditions in the field generally limit identification to visual methods, including using a magnifying glass for fine-grained rocks. Visual inspection assesses properties such as colour, composition, grain size, and structure. The attributes of rocks reflect their mineral and chemical composition, formation environment, and genesis. The colour of rock reflects its chemical composition. But these analysis is time taken process to identify the rocks.Its application here has effectively identified rock types from images captured in the field. This paper proposes an accurate approach for identifying rock types in the field based on image analysis using deep convolutional neural networks. Solution: Deep learning is receiving significant research attention for pattern recognition and machine learning. Its application here has effectively identified rock types from images captured in the field. This paper proposes an accurate approach for identifying rock types in the field based on image analysis using deep convolutional neural networks. The results show that the proposed approach based on deep learning represents an improvement in intelligent rock-type identification and solves several difficulties facing the automated identification of rock types in the field.Who are experienced in the field of geological they can identify the rocks easily. But who are new to the field, it can help to identify the type of rock.
SmartPracticeschool/llSPS-INT-3224-Rock-identification-using-deep-convolution-neural-network
Rock identification using deep convolution neural network
sunyingjian/AI-in-well-logging
人工智能在石油测井上的应用包括采用机器学习，深度学习等相关方法进行岩性识别与相关测井曲线的回归。The application of artificial intelligence in well logging includes the use of machine learning, deep learning and other related methods for lithology identification and regression of related well logging data.