為您找到相關(guān)結(jié)果73個(gè)
Python(TensorFlow框架)實(shí)現(xiàn)手寫數(shù)字識(shí)別系統(tǒng)的方法_python_腳本之家
本層訓(xùn)練參數(shù)共6×(5×5+1)=156個(gè),每個(gè)像素點(diǎn)都是由上層5×5=25個(gè)像素點(diǎn)和1個(gè)閾值連接計(jì)算所得,共28×28×156=122304個(gè)連接。 S2層是對(duì)應(yīng)上述6個(gè)特征映射的降采樣層(pooling層)。pooling層的實(shí)現(xiàn)方法有兩種,分別是max-pooling和mean-pooling,LeNet-5采用的是mean-pooling,即取n×n區(qū)域內(nèi)像素的均值。C1通...
www.dbjr.com.cn/article/1410...htm 2025-6-4
Python MNIST手寫體識(shí)別詳解與試練_python_腳本之家
# Build LeNet-5 model=Sequential() model.add(Conv2D(filters=6, kernel_size=(5,5), padding='valid', input_shape=(28,28,1), activation='relu'))# C1 model.add(MaxPooling2D(pool_size=(2,2)))# S2 model.add(Conv2D(filters=16, kernel_size=(5,5), padding='valid', activation='re...
www.dbjr.com.cn/article/2274...htm 2025-6-9
使用Tensorflow實(shí)現(xiàn)可視化中間層和卷積層_python_腳本之家
用簡(jiǎn)單的LeNet網(wǎng)絡(luò)訓(xùn)練MNIST數(shù)據(jù)集作為示例: 1 2 3 4 5 6 7 8 x=tf.placeholder(tf.float32, [None,784]) x_image=tf.reshape(x, [-1,28,28,1]) W_conv1=weight_variable([5,5,1,32])# 第一個(gè)卷積層的32個(gè)卷積核 b_conv1=bias_variable([32]) ...
www.dbjr.com.cn/article/1791...htm 2025-5-18
caffe的python接口之手寫數(shù)字識(shí)別mnist實(shí)例_python_腳本之家
def Lenet(img_list,batch_size,include_acc=False): #第一層,數(shù)據(jù)輸入層,以ImageData格式輸入 data, label = L.ImageData(source=img_list, batch_size=batch_size, ntop=2,root_folder=root, transform_param=dict(scale= 0.00390625)) #第二層:卷積層 conv1=L.Convolution(data, kernel_size=5, strid...
www.dbjr.com.cn/article/2534...htm 2025-6-4
PyTorch實(shí)現(xiàn)模型剪枝的方法_python_腳本之家
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 model_2 = LeNet().to(device=device) # 首先打印初始化模型的狀態(tài)字典 print(model_2.state_dict().keys()) # 構(gòu)建參數(shù)集合, 決定哪些層, 哪些參數(shù)集合參與剪枝 parameters_to_prune = ( (model_2.conv1, 'weight'), (model_2.conv2, '...
www.dbjr.com.cn/python/319102s...htm 2025-6-6
Ubuntu14.04搭建Caffe(僅CPU)詳解教程_Linux_腳本之家
5.在Mnist運(yùn)行Lenet 獲取數(shù)據(jù)源 1 2 ./data/mnist/get_mnist.sh ./examples/mnist/create_mnist.sh 因?yàn)槭荂PU運(yùn)行,所以修改在examples文件下的Mnist下的lenet_solver.prototxt中的solver_mode:CPU 1 solver_mode: CPU 訓(xùn)練模型 1 ./examples/mnist/train_lenet.sh ...
www.dbjr.com.cn/article/961...htm 2025-5-29
Python FastAPI入門安裝使用_python_腳本之家
1 2 3 4 5 6 7 8 9 10 11 12 13 14 from enum import Enum from fastapi import FastAPI class ModelName(str, Enum): alexnet = "alexnet" resnet = "resnet" lenet = "lenet" app = FastAPI() @app.get("/models/{model_name}") async def get_model(model_name: ModelName): if model...
www.dbjr.com.cn/python/337537x...htm 2025-5-25