• Umesha D K

Image classification and segmentation are two fundamental tasks in computer vision with a wide range of applications. Deep learning has revolutionized these tasks, achieving state-of-the-art results on many challenging benchmarks. This paper presents a patent analysis of recent advances in image classification and segmentation using deep learning. We analyse several patents from leading companies and academic institutions to identify key trends and innovations in this field. Our analysis shows that deep learning architectures such as convolutional neural networks (CNNs) and attention mechanisms are widely used in these patents. We also identify the development of new deep learning architectures specifically tailored for image classification and segmentation tasks as a key trend. The patented technologies have the potential to revolutionize the way that images are classified and segmented.

image classification, image segmentation, deep learning, patent analysis, attention mechanisms, spatial transformers, multi-scale feature fusion, multi-stage cascaded learning.

"A Survey of Deep Learning Patents for Image Classification and Segmentation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 10, page no.h591-h596, October-2023, Available :http://www.jetir.org/papers/JETIR2310674.pdf

"A Survey of Deep Learning Patents for Image Classification and Segmentation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 10, page no. pph591-h596, October-2023, Available at : http://www.jetir.org/papers/JETIR2310674.pdf