DEEP LEARNING TECHNIQUES FOR IMAGE AND SPEECH RECOGNITION
Keywords:
Deep Learning, Image Recognition, Speech Recognition, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN)Abstract
Deep learning has revolutionized the field of artificial intelligence, enabling significant advancements in image and speech recognition tasks. This paper provides a comprehensive review of deep learning techniques utilized in these domains, focusing on architectures such as convolutional neural networks (CNNs) for image recognition and recurrent neural networks (RNNs) including Long Short-Term Memory (LSTM) for speech recognition. The paper discusses recent state-of-the-art models, datasets, challenges, and applications relevant to Pakistan’s technological landscape. Additionally, experimental results are presented through comparative graphs illustrating accuracy improvements and model performances. The study concludes by highlighting future research directions to further optimize deep learning applications for robust recognition systems.
