Beijing Baidu Netcom Science Technology Co., Ltd

Qingqing Dang

Yanjun Ma

Xiaoguang Hu

Haifeng Wang

Dianhai Yu

Tian Wu

Qiwen Liu

Sheng Guo

Chunyu Zhang

Guanghua Yu

Can Wen

Guanzhong Wang

Kaipeng Deng

Haoshuang Wang

Lielin Jiang

Embodiments of the present disclosure provide a method and apparatus of training a model, an electronic device, a storage medium and a development system, which relate to a field of deep learning. The method may include calling a training preparation component to set at least a loss function and an optimization function for training the model, in response to determining that a training preparation instruction is received. The method further includes calling a training component to set a first data reading component, in response to determining that a training instruction is received. The first data reading component is configured to load a training data set for training the model. In addition, the method may further include training the model based on the training data set from the first data reading component, by using the loss function and the optimization function through the training component.

Model development tool to train, evaluate and predict with deep learning by selecting functions

A method for detecting an object in an image includes: obtaining an image to be detected; generating a plurality of feature maps based on the image to be detected by a plurality of feature extracting networks in a neural network model trained for object detection, in which the plurality of feature extracting networks are connected sequentially, and input data of a latter feature extracting network in the plurality of feature extracting networks is based on output data and input data of a previous feature extracting network; and generating an object detection result based on the plurality of feature maps by an object detecting network in the neural network model.

Method and device for detecting an object in an image

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Qingqing Dang