100套大数据可视化炫酷大屏Html5模板;包含行业:社区、物业、政务、交通、金融银行等,全网最新、最多,最全、最酷、最炫大数据可视化模板。陆续更新中
100套大数据可视化炫酷大屏Html5模板;包含行业:社区、物业、政务、交通、金融银行等,全网最新、最多,最全、最酷、最炫大数据可视化模板。陆续更新中
同步更新官方最新版 Yolov5 ,发行版提供模型下载地址, Yolo8已发布: https://gitee.com/monkeycc/ultralytics
Tumour is formed in human body by abnormal cell multiplication in the tissue. Early detection of tumors and classifying them to Benign and malignant tumours is important in order to prevent its further growth. MRI (Magnetic Resonance Imaging) is a medical imaging technique used by radiologists to study and analyse medical images. Doing critical analysis manually can create unnecessary delay and also the accuracy for the same will be very less due to human errors. The main objective of this project is to apply machine learning techniques to make systems capable enough to perform such critical analysis faster with higher accuracy and efficiency levels. This research work is been done on te existing architecture of convolution neural network which can identify the tumour from MRI image. The Convolution Neural Network was implemented using Keras and TensorFlow, accelerated by NVIDIA Tesla K40 GPU. Using REMBRANDT as the dataset for implementation, the Classification accuracy accuired for AlexNet and ZFNet are 63.56% and 84.42% respectively.
Unity无人机仿真github项目
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