6 Result(s)
within
Chapter
Amit Joshi
Machine Learning
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Chapter
Performance Analysis of Memory-Efficient Vision Transformers in Brain Tumor Segmentation
Convolutional neural networks are the most in demand solution for computer-aided medical image-segmentation applications and have attained excellent results. In recent years, transformer architectures, convent...
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Chapter
Medical Image Synthesis Using Generative Adversarial Networks
The diagnostic capabilities in medical imaging domain saw significant improvements triggered by advances in deep learning in the past few years. The ophthalmology analysis of retinal networks gives information...
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Chapter
Unlocking New Possibilities in Drug Discovery: A GAN-Based Approach
Drug discovery refers to the process of identifying and develo** new chemical compounds, to create medications that can treat or cure diseases. In the process of drug discovery, one of the major obstacles is...
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Chapter
Early Detection of Diabetic Retinopathy Using Deep Learning
Diabetic retinopathy is a major cause of blindness in diabetic individuals aged 25–65, where lesions on the retina caused by weakened blood vessels can lead to visual loss and even total blindness. Current man...
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Chapter and Conference Paper
Reflectance Mode Fluorescence Optical Tomography with Consumer-Grade Cameras
Efficient algorithms for solving inverse optical tomography problems with noisy and sparse measurements are a major challenge for near-infrared fluorescence guided surgery. To address that challenge, we propos...
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Chapter and Conference Paper
Land Use Land Cover Classification Using Different ML Algorithms on Sentinel-2 Imagery
Land use land cover analysis is important in many remote sensing applications such as change detection and resource monitoring. It is an efficient means to manage and analyse land transformation. Best machine ...
