CNN (or Convolutional Neural Network) is the building block of all Computer Vision applications. Applications like self-driving cars, object recognition, face recognition, etc.

Notably, CNN-LSTM hybrid models have been instrumental in capturing both local and temporal features of speech, thereby enhancing recognition accuracy across various datasets [1].

A CIFAR neural network is a type of CNN that is widely used in image recognition tasks. It consists of two main types of layers: convolutional layers and pooling layers, which are both utilized to ...

Convolutional neural networks (CNNs) are a class of deep neural networks commonly used in computer vision tasks such as image and video recognition, object detection and image segmentation.

Emotion recognition in speech, driven by advances in neural network methodologies, has emerged as a pivotal domain in human–machine interaction.