What is the limitation of neural networks?

Disadvantages include its “black box” nature, greater computational burden, proneness to overfitting, and the empirical nature of model development. An overview of the features of neural networks and logistic regression is presented, and the advantages and disadvantages of using this modeling technique are discussed.

What are the advantages and disadvantages of computer vision?

The reduction of costs: time and error rate are reduced in the process of Computer Imagining. It reduces the cost of hire and train special staff to do the activities that computers will do as hundreds of workers. Despite all the advantages of computer vision thanks to the capacity of Machine Learning, we have to consider some disadvantages:

What do we talk about in computer vision?

We talk about automation, controlling, precise measuring and recognition. The technology in Computer Vision is analyses and measures the images that a camera can capture. For example, in the case of a surveillance camera, it can recognise smoke as an automated premise. It is useful to activate an alarm and prevent possible damages.

What are the advantages of computers and cameras over humans?

Reliability: computers and cameras don’t have the human factor of tiredness, which is eliminated in them. The efficiency is usually the same, it doesn’t depend on external factors such as illness or sentimental status. Accuracy: the precision of Computer Imagining, and Computer Vision will ensure a better accuracy on the final product.

What happens when computer vision and image processing fail?

Failing in image processing: when the device fails because of a virus or other software issues, it is highly probable that Computer Vision and image processing will fail. But if we do not solve the problem, the functions of the device can dissapear. It can froze the entire production in the case of warehouses.