Q:

multiple object detection in an image

I wanted to ask you a question about image classification.
Actually I am making a image classifier and I am using convolutuional neural networks with keras and tensorflow as backend.
my question is how to identify multiple objects in an image.
I've tried convolutional neural network with activation function sigmoid and loss - binary_crossentropy but I am not satisfied with. 

A:

I'm assuming you are using a simple CNN, in which case, for multiple objects, it will only identify a single object. The problem isn't the activation or the loss, it's the architecture. You need to use something like a RCNN (Faster RCNN, YOLO, SSD, or the current SOTA: Mask RCNN).
In case you are using an RCNN model, and the detection isn't accurate enough, you would need to post more details about your network for anyone to trouble suggest improvements.

